803 resultados para COMPUTER SCIENCE, INFORMATION SYSTEMS


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This article has been extracted from the results of a thesis entitled “Potential bioelectricity production of the Madrid Community Agricultural Regions based on rye and triticale biomass.” The aim was, first, to quantify the potential of rye (Secale Cereale L.) and triticale ( Triticosecale Aestivum L.) biomass in each of the Madrid Community agricultural regions, and second, to locate the most suitable areas for the installation of power plants using biomass. At least 17,339.9 t d.m. of rye and triticale would be required to satisfy the biomass needs of a 2.2 MW power plant, (considering an efficiency of 21.5%, 8,000 expected operating hours/year and a biomass LCP of 4,060 kcal/kg for both crops), and 2,577 ha would be used (which represent 2.79% of the Madrid Community fallow dry land surface). Biomass yields that could be achieved in Madrid Community using 50% of the fallow dry land surface (46,150 ha representing 5.75% of the Community area), based on rye and triticale crops, are estimated at 84,855, 74,906, 70,109, 50,791, 13,481, and 943 t annually for the Campiña, Vegas, Sur Occidental, Área Metropolitana, Lozoya-Somosierra, and Guadarrama regions. The latter represents a bioelectricity potential of 10.77, 9.5, 8.9, 6.44, 1.71, and 0.12 MW, respectively.

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The amount of genomic and proteomic data that is entered each day into databases and the experimental literature is outstripping the ability of experimental scientists to keep pace. While generic databases derived from automated curation efforts are useful, most biological scientists tend to focus on a class or family of molecules and their biological impact. Consequently, there is a need for molecular class-specific or other specialized databases. Such databases collect and organize data around a single topic or class of molecules. If curated well, such systems are extremely useful as they allow experimental scientists to obtain a large portion of the available data most relevant to their needs from a single source. We are involved in the development of two such databases with substantial pharmacological relevance. These are the GPCRDB and NucleaRDB information systems, which collect and disseminate data related to G protein-coupled receptors and intra-nuclear hormone receptors, respectively. The GPCRDB was a pilot project aimed at building a generic molecular class-specific database capable of dealing with highly heterogeneous data. A first version of the GPCRDB project has been completed and it is routinely used by thousands of scientists. The NucleaRDB was started recently as an application of the concept for the generalization of this technology. The GPCRDB is available via the WWW at http://www.gpcr.org/7tm/ and the NucleaRDB at http://www.receptors.org/NR/.

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The technology innovation (TI) in the health system has been confirmed as the best format to share information and to facilitate the communication between all the actors involved in the chronic patients´ care.

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Purpose – The purpose of this paper is to analyse Information Systems outsourcing success, measuring the latter according to the satisfaction level achieved by users and taking into account three success factors: the role played by the client firm’s top management; the relationships between client and provider; and the degree of outsourcing. Design/methodology/approach – A survey was carried out by means of a questionnaire answered by 398 large Spanish firms. Its results were examined using the partial least squares software and through the proposal of a structural equation model. Findings – The conclusions reveal that the perceived benefits play a mediating role in outsourcing satisfaction and also that these benefits can be grouped together into three categories: strategic; economic; and technological ones. Originality/value – The study identifies how some success factors will be more influent than others depending which type of benefits are ultimately sought with outsourcing.

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Despite the proliferation of academic research on information systems outsourcing, not many studies analyze the characteristics of outsourcing contracts. This research aims to provide an in-depth description of information systems outsourcing. An additional objective is to examine how these characteristics evolve over time. Finally, this study reports on the usefulness of measuring such characteristics over time to assess the maturity level of the information systems outsourcing. This study gathers the data from the responses of the information systems managers of the largest Spanish firms to a questionnaire. This longitudinal study covers 12 years of research and compares authors' previous research results with the results of this study.

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Partial differential equation (PDE) solvers are commonly employed to study and characterize the parameter space for reaction-diffusion (RD) systems while investigating biological pattern formation. Increasingly, biologists wish to perform such studies with arbitrary surfaces representing ‘real’ 3D geometries for better insights. In this paper, we present a highly optimized CUDA-based solver for RD equations on triangulated meshes in 3D. We demonstrate our solver using a chemotactic model that can be used to study snakeskin pigmentation, for example. We employ a finite element based approach to perform explicit Euler time integrations. We compare our approach to a naive GPU implementation and provide an in-depth performance analysis, demonstrating the significant speedup afforded by our optimizations. The optimization strategies that we exploit could be generalized to other mesh based processing applications with PDE simulations.

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In this article we present a computational framework for isolating spatial patterns arising in the steady states of reaction-diffusion systems. Such systems have been used to model many different phenomena in areas such as developmental and cancer biology, cell motility and material science. Often one is interested in identifying parameters which will lead to a particular pattern. To attempt to answer this, we compute eigenpairs of the Laplacian on a variety of domains and use linear stability analysis to determine parameter values for the system that will lead to spatially inhomogeneous steady states whose patterns correspond to particular eigenfunctions. This method has previously been used on domains and surfaces where the eigenvalues and eigenfunctions are found analytically in closed form. Our contribution to this methodology is that we numerically compute eigenpairs on arbitrary domains and surfaces. Here we present various examples and demonstrate that mode isolation is straightforward especially for low eigenvalues. Additionally we see that if two or more eigenvalues are in a permissible range then the inhomogeneous steady state can be a linear combination of the respective eigenfunctions. Finally we show an example which suggests that pattern formation is robust on similar surfaces in cases that the surface either has or does not have a boundary.

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The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.