941 resultados para open source seismic data processing packages
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Surface geological mapping, laboratory measurements of rock properties, and seismic reflection data are integrated through three-dimensional seismic modeling to determine the likely cause of upper crustal reflections and to elucidate the deep structure of the Penninic Alps in eastern Switzerland. Results indicate that the principal upper crustal reflections recorded on the south end of Swiss seismic line NFP20-EAST can be explained by the subsurface geometry of stacked basement nappes. In addition, modeling results provide improvements to structural maps based solely on surface trends and suggest the presence of previously unrecognized rock units in the subsurface. Construction of the initial model is based upon extrapolation of plunging surface. structures; velocities and densities are established by laboratory measurements of corresponding rock units. Iterative modification produces a best fit model that refines the definition of the subsurface geometry of major structures. We conclude that most reflections from the upper 20 km can be ascribed to the presence of sedimentary cover rocks (especially carbonates) and ophiolites juxtaposed against crystalline basement nappes. Thus, in this area, reflections appear to be principally due to first-order lithologic contrasts. This study also demonstrates not only the importance of three-dimensional effects (sideswipe) in interpreting seismic data, but also that these effects can be considered quantitatively through three-dimensional modeling.
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Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface-based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies-based subsurface parameterization is developed. The Bayesian-McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two-dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.
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The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.
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Nowadays, when a user is planning a touristic route is very difficult to find out which are the best places to visit. The user has to choose considering his/her preferences due to the great quantity of information it is possible to find in the web and taking into account it is necessary to do a selection, within small time because there is a limited time to do a trip. In Itiner@ project, we aim to implement Semantic Web technology combined with Geographic Information Systems in order to offer personalized touristic routes around a region based on user preferences and time situation. Using ontologies it is possible to link, structure, share data and obtain the result more suitable for user's preferences and actual situation with less time and more precisely than without ontologies. To achieve these objectives we propose a web page combining a GIS server and a touristic ontology. As a step further, we also study how to extend this technology on mobile devices due to the raising interest and technological progress of these devices and location-based services, which allows the user to have all the route information on the hand when he/she does a touristic trip. We design a little application in order to apply the combination of GIS and Semantic Web in a mobile device.
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This report describes a short-term study undertaken to investigate the potential for using dense three-dimensional (3D) point clouds generated from light detection and ranging (LIDAR) and photogrammetry to assess roadway roughness. Spatially continuous roughness maps have potential for the identification of localized roughness features, which would be a significant improvement over traditional profiling methods. This report specifically illustrates the use of terrestrial laser scanning (TLS) and photogrammetry using a process known as structure from motion (SFM) to acquire point clouds and illustrates the use of these point clouds in evaluating road roughness. Five roadway sections were chosen for scanning and testing: three gravel road sections, one portland cement concrete (PCC) section, and one asphalt concrete (AC) section. To compare clouds obtained from terrestrial laser scanning and photogrammetry, the coordinates of the clouds for the same section on the same date were matched using open source computer code. The research indicates that the technologies described are very promising for evaluating road roughness. The major advantage of both technologies is the large amount of data collected, which allows the evaluation of the full surface. Additional research is needed to further develop the use of dense 3D point clouds for roadway assessment.
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Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge.
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DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser.
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In this paper we discuss and analyze the process of using a learning object repository and building a social network on the top of it, including aspects related to open source technologies, promoting the use of the repository by means of social networks and helping learners to develop their own learning paths.
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The Universitat Oberta de Catalunya (Open University of Catalonia, UOC) is an online university that makes extensive use of information and communication technologies to provide education. Ever since its establishment in 1995, the UOC has developed and tested methodologies and technological support services to meet the educational challenges posed by its student community and its teaching and management staff. The know-how it has acquired in doing so is the basis on which it has created the Open Apps platform, which is designed to provide access to open source technical applications, information on successful learning and teaching experiences, resources and other solutions, all in a single environment. Open Apps is an open, online catalogue, the content of which is available to all students for learning purposes, all IT professionals for downloading and all teachers for reusing.To contribute to the transfer of knowledge, experience and technology, each of the platform¿s apps comes with full documentation, plus information on cases in which it has been used and related tools. It is hoped that such transfer will lead to the growth of an external partner network, and that this, in turn, will result in improvements to the applications and teaching/learning practices, and in greater scope for collaboration.Open Apps is a strategic project that has arisen from the UOC's commitment to the open access movement and to giving knowledge and technology back to society, as well as its firm belief that sustainability depends on communities of interest.
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Peer-reviewed
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With nearly 2,000 free and open source software (FLOSS) licenses, software license proliferation¿ can be a major headache for software development organizations trying to speed development through software component reuse, as well as companies redistributing software packages as components of their products. Scope is one problem: from the Free Beer license to the GPL family of licenses to platform-specific licenses such as Apache and Eclipse, the number and variety of licenses make it difficult for companies to ¿do the right thing¿ with respect to the software components in their products and applications. In addition to the sheer number of licenses, each license carries within it the author¿s specific definition of how the software can be used and re-used. Permissive licenses like BSD and MIT make it easy; software can be redistributed and developers can modify code without the requirement of making changes publicly available. Reciprocal licenses, on the other hand, place varying restrictions on re-use and redistribution. Woe to the developer who snags a bit of code after a simple web search without understanding the ramifications of license restrictions.
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Extensible Dependency Grammar (XDG; Debusmann, 2007) is a flexible, modular dependency grammarframework in which sentence analyses consist of multigraphs and processing takes the form of constraint satisfaction. This paper shows how XDGlends itself to grammar-driven machine translation and introduces the machinery necessary for synchronous XDG. Since the approach relies on a shared semantics, it resembles interlingua MT.It differs in that there are no separateanalysis and generation phases. Rather, translation consists of the simultaneousanalysis and generation of a single source-target sentence.
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Tapahtumankäsittelyä pidetään yleisesti eräänä luotettavan tietojenkäsittelyn perusvaatimuksena. Tapahtumalla tarkoitetaan operaatiosarjaa, jonka suoritusta voidaan pitää yhtenä loogisena toimenpiteenä. Tapahtumien suoritukselle on asetettu neljä perussääntöä, joista käytetään lyhennettä ACID. Hajautetuissa järjestelmissä tapahtumankäsittelyn tarve kasvaa entisestään, sillä toimenpiteiden onnistumista ei voida varmistaa pelkästään paikallisten menetelmien avulla. Hajautettua tapahtumankäsittelyä on yritetty standardoida useaan otteeseen, muttayrityksistä huolimatta siitä ei ole olemassa yleisesti hyväksyttyjä ja avoimia standardeja. Lähimpänä tällaisen standardin asemaa on todennäköisesti X/Open DTP-standardiperhe ja varsinkin siihen kuuluva XA-standardi. Tässä työssä on lisäksi tutkittu, kuinka Intellitel ONE-järjestelmän valmistajariippumatonta tietokanta-arkkitehtuuria tulisi kehittää, kun tavoitteena on mahdollistaa sen avulla suoritettavien tapahtumankäsittelyä vaativien sovellusten käyttäminen.
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Gaia is the most ambitious space astrometry mission currently envisaged and is a technological challenge in all its aspects. We describe a proposal for the payload data handling system of Gaia, as an example of a high-performance, real-time, concurrent, and pipelined data system. This proposal includes the front-end systems for the instrumentation, the data acquisition and management modules, the star data processing modules, and the payload data handling unit. We also review other payload and service module elements and we illustrate a data flux proposal.