New data on the ophiolitic VMS deposits of Moeche (Cabo Ortegal Complex, NW Spain)

As a result of the variscan collision, several allochtonous complexes were emplaced on the Iberian margin in Devonian times, among them the Cabo Ortegal Complex comprising the Moeche ophiolitic sequence. Copper has been won from several mines (Piquitos I & II, Barqueira, Maruxa) from disseminated ores and thin massive sulphide layers in the Moeche Unit, a strongly deformed meta-volcanic sequence comprising mainly quartz-chlorite schists and mylonites, which defines the top of the ophiolite. The ores were metamorphosed and strongly deformed under brittle conditions (for pyrite), but their textures are often apparently post-deformational, due to very common solution-transfer processes; they are composed mostly of pyrite and chalcopyrite, with minor sphalerite, pyrrhotite, etc., and with traces of native gold and PGE. The geology, mineralogy, and geochemistry of the orebodies relate closely to VMS of the Cu-Zn (Cyprus) type. Fluid inclusion studies allowed an estimation of metamorphic conditions at pressures of 2/2’5 kb and T 325/350ºC. New determinations using the chlorite geothermometer yield temperatures around 320 ºC, corresponding to pressures near 2 kb according to the isochores deduced from the fluid inclusion study, although in the Barqueira mine higher temperatures, up to 350 ºC, are found, corresponding to presssures up to 2’5 kb. Pb isotopic compositions of pyrite point to a double source of Pb, i.e. a main mantle and a subordinate crustal source. The values for 87SR/86Sr in pyrite support this interpretation, but some results suggest later mobilization in an open system, corresponding to solution-transfer. Age determinations of pyrite deduced from the Pb isotope uranogenic graph, ≈ 480 Ma, do not fit with the metamorphic ages published for the Moeche Unit, and might point to the age of Pb extraction from the mantle.

A new approach for publishing workflows: abstractions, standards, and linked data

In recent years, a variety of systems have been developed that export the workflows used to analyze data and make them part of published articles. We argue that the workflows that are published in current approaches are dependent on the specific codes used for execution, the specific workflow system used, and the specific workflow catalogs where they are published. In this paper, we describe a new approach that addresses these shortcomings and makes workflows more reusable through: 1) the use of abstract workflows to complement executable workflows to make them reusable when the execution environment is different, 2) the publication of both abstract and executable workflows using standards such as the Open Provenance Model that can be imported by other workflow systems, 3) the publication of workflows as Linked Data that results in open web accessible workflow repositories. We illustrate this approach using a complex workflow that we re-created from an influential publication that describes the generation of 'drugomes'.

A Model-based Repository for Open Source Service and Component Integration.

Open source is a software development paradigm that has seen a huge rise in recent years. It reduces IT costs and time to market, while increasing security and reliability. However, the difficulty in integrating developments from different communities and stakeholders prevents this model from reaching its full potential. This is mainly due to the challenge of determining and locating the correct dependencies for a given software artifact. To solve this problem we propose the development of an extensible software component repository based upon models. This repository should be capable of solving the dependencies between several components and work with already existing repositories to access the needed artifacts transparently. This repository will also be easily expandable, enabling the creation of modules that support new kinds of dependencies or other existing repository technologies. The proposed solution will work with OSGi components and use OSGi itself.

Linked Opinions: Describing Sentiments on the Structured Web of Data

In the paper we report on the results of our experiments on the construction of the opinion ontology. Our aim is to show the benefits of publishing in the open, on the Web, the results of the opinion mining process in a structured form. On the road to achieving this, we attempt to answer the research question to what extent opinion information can be formalized in a unified way. Furthermore, as part of the evaluation, we experiment with the usage of Semantic Web technologies and show particular use cases that support our claims.

Exploiting Structured Linked Data in Enterprise Knowledge Management Systems: An Idea Management Case Study

In parallel to the effort of creating Open Linked Data for the World Wide Web there is a number of projects aimed for developing the same technologies but in the context of their usage in closed environments such as private enterprises. In the paper, we present results of research on interlinking structured data for use in Idea Management Systems - a still rare breed of knowledge management systems dedicated to innovation management. In our study, we show the process of extending an ontology that initially covers only the Idea Management System structure towards the concept of linking with distributed enterprise data and public data using Semantic Web technologies. Furthermore we point out how the established links can help to solve the key problems of contemporary Idea Management Systems

The Landscape of Ontology Reuse in Linked Data

Abstract. The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies for describing different domains. Ac-cording to LD principles, developers should reuse as many available terms as possible to describe their data. Importing ontologies or referring to their terms’ URIs are the two main ways to reuse knowledge from available ontologies. In this paper, we have analyzed 18589 terms appearing within 196 ontologies in-cluded in the Linked Open Vocabularies (LOV) registry with the aim of under-standing the current state of ontology reuse in the LD context. In order to char-acterize the landscape of ontology reuse in this context, we have extracted sta-tistics about currently reused elements, calculated ratios for reuse, and drawn graphs about imports and references between ontologies. Keywords: ontology, vocabulary, reuse, linked data, ontology import

Adapting autonomously classification data mining algorithms for ubiquitous devices

Abstract Due to recent scientific and technological advances in information sys¬tems, it is now possible to perform almost every application on a mobile device. The need to make sense of such devices more intelligent opens an opportunity to design data mining algorithm that are able to autonomous execute in local devices to provide the device with knowledge. The problem behind autonomous mining deals with the proper configuration of the algorithm to produce the most appropriate results. Contextual information together with resource information of the device have a strong impact on both the feasibility of a particu¬lar execution and on the production of the proper patterns. On the other hand, performance of the algorithm expressed in terms of efficacy and efficiency highly depends on the features of the dataset to be analyzed together with values of the parameters of a particular implementation of an algorithm. However, few existing approaches deal with autonomous configuration of data mining algorithms and in any case they do not deal with contextual or resources information. Both issues are of particular significance, in particular for social net¬works application. In fact, the widespread use of social networks and consequently the amount of information shared have made the need of modeling context in social application a priority. Also the resource consumption has a crucial role in such platforms as the users are using social networks mainly on their mobile devices. This PhD thesis addresses the aforementioned open issues, focusing on i) Analyzing the behavior of algorithms, ii) mapping contextual and resources information to find the most appropriate configuration iii) applying the model for the case of a social recommender. Four main contributions are presented: - The EE-Model: is able to predict the behavior of a data mining algorithm in terms of resource consumed and accuracy of the mining model it will obtain. - The SC-Mapper: maps a situation defined by the context and resource state to a data mining configuration. - SOMAR: is a social activity (event and informal ongoings) recommender for mobile devices. - D-SOMAR: is an evolution of SOMAR which incorporates the configurator in order to provide updated recommendations. Finally, the experimental validation of the proposed contributions using synthetic and real datasets allows us to achieve the objectives and answer the research questions proposed for this dissertation.

Idea relationship analysis in open innovation crowdsourcing systems

Idea Management Systems are an implementation of open innovation notion in the Web environment with the use of crowdsourcing techniques. In this area, one of the popular methods for coping with large amounts of data is duplicate de- tection. With our research, we answer a question if there is room to introduce more relationship types and in what degree would this change affect the amount of idea metadata and its diversity. Furthermore, based on hierarchical dependencies between idea relationships and relationship transitivity we propose a number of methods for dataset summarization. To evaluate our hypotheses we annotate idea datasets with new relationships using the contemporary methods of Idea Management Systems to detect idea similarity. Having datasets with relationship annotations at our disposal, we determine if idea features not related to idea topic (e.g. innovation size) have any relation to how annotators perceive types of idea similarity or dissimilarity.

Data Fusion based on Game Theory for Speaker Diarization

A novel algorithm based on bimatrix game theory has been developed to improve the accuracy and reliability of a speaker diarization system. This algorithm fuses the output data of two open-source speaker diarization programs, LIUM and SHoUT, taking advantage of the best properties of each one. The performance of this new system has been tested by means of audio streams from several movies. From preliminary results on fragments of five movies, improvements of 63% in false alarms and missed speech mistakes have been achieved with respect to LIUM and SHoUT systems working alone. Moreover, we also improve in a 20% the number of recognized speakers, getting close to the real number of speakers in the audio stream

Development of a wake model for wind farms based on an open source CFD solver. Strategies on parabolization and turbulence modeling

Wake effect represents one of the most important aspects to be analyzed at the engineering phase of every wind farm since it supposes an important power deficit and an increase of turbulence levels with the consequent decrease of the lifetime. It depends on the wind farm design, wind turbine type and the atmospheric conditions prevailing at the site. Traditionally industry has used analytical models, quick and robust, which allow carry out at the preliminary stages wind farm engineering in a flexible way. However, new models based on Computational Fluid Dynamics (CFD) are needed. These models must increase the accuracy of the output variables avoiding at the same time an increase in the computational time. Among them, the elliptic models based on the actuator disk technique have reached an extended use during the last years. These models present three important problems in case of being used by default for the solution of large wind farms: the estimation of the reference wind speed upstream of each rotor disk, turbulence modeling and computational time. In order to minimize the consequence of these problems, this PhD Thesis proposes solutions implemented under the open source CFD solver OpenFOAM and adapted for each type of site: a correction on the reference wind speed for the general elliptic models, the semi-parabollic model for large offshore wind farms and the hybrid model for wind farms in complex terrain. All the models are validated in terms of power ratios by means of experimental data derived from real operating wind farms.

Open Technologies for prototyping the Internet of Things

The worldwide "hyper-connection" of any object around us is the challenge that promises to cover the paradigm of the Internet of Things. If the Internet has colonized the daily life of more than 2000 million1 people around the globe, the Internet of Things faces of connecting more than 100000 million2 "things" by 2020. The underlying Internet of Things’ technologies are the cornerstone that promises to solve interrelated global problems such as exponential population growth, energy management in cities, and environmental sustainability in the average and long term. On the one hand, this Project has the goal of knowledge acquisition about prototyping technologies available in the market for the Internet of Things. On the other hand, the Project focuses on the development of a system for devices management within a Wireless Sensor and Actuator Network to offer some services accessible from the Internet. To accomplish the objectives, the Project will begin with a detailed analysis of various “open source” hardware platforms to encourage creative development of applications, and automatically extract information from the environment around them for transmission to external systems. In addition, web platforms that enable mass storage with the philosophy of the Internet of Things will be studied. The project will culminate in the proposal and specification of a service-oriented software architecture for embedded systems that allows communication between devices on the network, and the data transmission to external systems. Furthermore, it abstracts the complexities of hardware to application developers. RESUMEN. La “hiper-conexión” a nivel mundial de cualquier objeto que nos rodea es el desafío al que promete dar cobertura el paradigma de la Internet de las Cosas. Si la Internet ha colonizado el día a día de más de 2000 millones1 de personas en todo el planeta, la Internet de las Cosas plantea el reto de conectar a más de 100000 millones2 de “cosas” para el año 2020. Las tecnologías subyacentes de la Internet de las Cosas son la piedra angular que prometen dar solución a problemas globales interrelacionados como el crecimiento exponencial de la población, la gestión de la energía en las ciudades o la sostenibilidad del medioambiente a largo plazo. Este Proyecto Fin de Carrera tiene como principales objetivos por un lado, la adquisición de conocimientos acerca de las tecnologías para prototipos disponibles en el mercado para la Internet de las Cosas, y por otro lado el desarrollo de un sistema para la gestión de dispositivos de una red inalámbrica de sensores que ofrezcan unos servicios accesibles desde la Internet. Con el fin de abordar los objetivos marcados, el proyecto comenzará con un análisis detallado de varias plataformas hardware de tipo “open source” que estimulen el desarrollo creativo de aplicaciones y que permitan extraer de forma automática información del medio que les rodea para transmitirlo a sistemas externos para su posterior procesamiento. Por otro lado, se estudiarán plataformas web identificadas con la filosofía de la Internet de las Cosas que permitan el almacenamiento masivo de datos que diferentes plataformas hardware transfieren a través de la Internet. El Proyecto culminará con la propuesta y la especificación una arquitectura software orientada a servicios para sistemas empotrados que permita la comunicación entre los dispositivos de la red y la transmisión de datos a sistemas externos, así como facilitar el desarrollo de aplicaciones a los programadores mediante la abstracción de la complejidad del hardware.

An open-source simulation tool of grid-connected PV systems.

This paper will present an open-source simulation tool, which is being developed in the frame of an European research project1. The tool, whose final version will be freely available through a website, allows the modelling and the design of different types of grid-connected PV systems, such as large grid-connected plants and building-integrated installations. The tool is based on previous software developed by the IES-UPM2, whose models and energy losses scenarios have been validated in the commissioning of PV projects3 carried out in Spain, Portugal, France and Italy, whose aggregated capacity is nearly 300MW. This link between design and commissioning is one of the key points of tool presented here, which is not usually addressed by present commercial software. The tool provides, among other simulation results, the energy yield, the analysis and breakdown of energy losses, and the estimations of financial returns adapted to the legal and financial frameworks of each European country. Besides, educational facilities will be developed and integrated in the tool, not only devoted to learn how to use this software, but also to train the users on the best design PV systems practices. The tool will also include the recommendation of several PV community experts, which have been invited to identify present necessities in the field of PV systems simulation. For example, the possibility of using meteorological forecasts as input data, or modelling the integration of large energy storage systems, such as vanadium redox or lithium-ion batteries. Finally, it is worth mentioning that during the verification and testing stages of this software development, it will be also open to the suggestions received from the different actors of the PV community, such as promoters, installers, consultants, etc.

MIA - a free and open source software for gray scale medical image analysis

Background Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large. Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also accessable to researchers that have no background or little in software development because they take care of otherwise complex tasks. Specifically, the management of working memory is taken care of automatically, usually at the price of requiring more it. As a result, processing large data sets with these tools becomes increasingly difficult on work station class computers. One alternative to using these high level processing tools is the development of new algorithms in a languages like C++, that gives the developer full control over how memory is handled, but the resulting workflow for the prototyping of new algorithms is rather time intensive, and also not appropriate for a researcher with little or no knowledge in software development. Another alternative is in using command line tools that run image processing tasks, use the hard disk to store intermediate results, and provide automation by using shell scripts. Although not as convenient as, e.g. visual programming, this approach is still accessable to researchers without a background in computer science. However, only few tools exist that provide this kind of processing interface, they are usually quite task specific, and don’t provide an clear approach when one wants to shape a new command line tool from a prototype shell script. Results The proposed framework, MIA, provides a combination of command line tools, plug-ins, and libraries that make it possible to run image processing tasks interactively in a command shell and to prototype by using the according shell scripting language. Since the hard disk becomes the temporal storage memory management is usually a non-issue in the prototyping phase. By using string-based descriptions for filters, optimizers, and the likes, the transition from shell scripts to full fledged programs implemented in C++ is also made easy. In addition, its design based on atomic plug-ins and single tasks command line tools makes it easy to extend MIA, usually without the requirement to touch or recompile existing code. Conclusion In this article, we describe the general design of MIA, a general purpouse framework for gray scale image processing. We demonstrated the applicability of the software with example applications from three different research scenarios, namely motion compensation in myocardial perfusion imaging, the processing of high resolution image data that arises in virtual anthropology, and retrospective analysis of treatment outcome in orthognathic surgery. With MIA prototyping algorithms by using shell scripts that combine small, single-task command line tools is a viable alternative to the use of high level languages, an approach that is especially useful when large data sets need to be processed.