922 resultados para Data replication processes
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Replication Data Management (RDM) aims at enabling the use of data collections from several iterations of an experiment. However, there are several major challenges to RDM from integrating data models and data from empirical study infrastructures that were not designed to cooperate, e.g., data model variation of local data sources. [Objective] In this paper we analyze RDM needs and evaluate conceptual RDM approaches to support replication researchers. [Method] We adapted the ATAM evaluation process to (a) analyze RDM use cases and needs of empirical replication study research groups and (b) compare three conceptual approaches to address these RDM needs: central data repositories with a fixed data model, heterogeneous local repositories, and an empirical ecosystem. [Results] While the central and local approaches have major issues that are hard to resolve in practice, the empirical ecosystem allows bridging current gaps in RDM from heterogeneous data sources. [Conclusions] The empirical ecosystem approach should be explored in diverse empirical environments.
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Cover title.
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Item 247.
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Includes bibliography.
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Recently within the machine learning and spatial statistics communities many papers have explored the potential of reduced rank representations of the covariance matrix, often referred to as projected or fixed rank approaches. In such methods the covariance function of the posterior process is represented by a reduced rank approximation which is chosen such that there is minimal information loss. In this paper a sequential framework for inference in such projected processes is presented, where the observations are considered one at a time. We introduce a C++ library for carrying out such projected, sequential estimation which adds several novel features. In particular we have incorporated the ability to use a generic observation operator, or sensor model, to permit data fusion. We can also cope with a range of observation error characteristics, including non-Gaussian observation errors. Inference for the variogram parameters is based on maximum likelihood estimation. We illustrate the projected sequential method in application to synthetic and real data sets. We discuss the software implementation and suggest possible future extensions.
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This research presents several components encompassing the scope of the objective of Data Partitioning and Replication Management in Distributed GIS Database. Modern Geographic Information Systems (GIS) databases are often large and complicated. Therefore data partitioning and replication management problems need to be addresses in development of an efficient and scalable solution. ^ Part of the research is to study the patterns of geographical raster data processing and to propose the algorithms to improve availability of such data. These algorithms and approaches are targeting granularity of geographic data objects as well as data partitioning in geographic databases to achieve high data availability and Quality of Service(QoS) considering distributed data delivery and processing. To achieve this goal a dynamic, real-time approach for mosaicking digital images of different temporal and spatial characteristics into tiles is proposed. This dynamic approach reuses digital images upon demand and generates mosaicked tiles only for the required region according to user's requirements such as resolution, temporal range, and target bands to reduce redundancy in storage and to utilize available computing and storage resources more efficiently. ^ Another part of the research pursued methods for efficient acquiring of GIS data from external heterogeneous databases and Web services as well as end-user GIS data delivery enhancements, automation and 3D virtual reality presentation. ^ There are vast numbers of computing, network, and storage resources idling or not fully utilized available on the Internet. Proposed "Crawling Distributed Operating System "(CDOS) approach employs such resources and creates benefits for the hosts that lend their CPU, network, and storage resources to be used in GIS database context. ^ The results of this dissertation demonstrate effective ways to develop a highly scalable GIS database. The approach developed in this dissertation has resulted in creation of TerraFly GIS database that is used by US government, researchers, and general public to facilitate Web access to remotely-sensed imagery and GIS vector information. ^
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Currently the data storage industry is facing huge challenges with respect to the conventional method of recording data known as longitudinal magnetic recording. This technology is fast approaching a fundamental physical limit, known as the superparamagnetic limit. A unique way of deferring the superparamagnetic limit incorporates the patterning of magnetic media. This method exploits the use of lithography tools to predetermine the areal density. Various nanofabrication schemes are employed to pattern the magnetic material are Focus Ion Beam (FIB), E-beam Lithography (EBL), UV-Optical Lithography (UVL), Self-assembled Media Synthesis and Nanoimprint Lithography (NIL). Although there are many challenges to manufacturing patterned media, the large potential gains offered in terms of areal density make it one of the most promising new technologies on the horizon for future hard disk drives. Thus, this dissertation contributes to the development of future alternative data storage devices and deferring the superparamagnetic limit by designing and characterizing patterned magnetic media using a novel nanoimprint replication process called "Step and Flash Imprint lithography". As opposed to hot embossing and other high temperature-low pressure processes, SFIL can be performed at low pressure and room temperature. Initial experiments carried out, consisted of process flow design for the patterned structures on sputtered Ni-Fe thin films. The main one being the defectivity analysis for the SFIL process conducted by fabricating and testing devices of varying feature sizes (50 nm to 1 μm) and inspecting them optically as well as testing them electrically. Once the SFIL process was optimized, a number of Ni-Fe coated wafers were imprinted with a template having the patterned topography. A minimum feature size of 40 nm was obtained with varying pitch (1:1, 1:1.5, 1:2, and 1:3). The Characterization steps involved extensive SEM study at each processing step as well as Atomic Force Microscopy (AFM) and Magnetic Force Microscopy (MFM) analysis.
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Language provides an interesting lens to look at state-building processes because of its cross-cutting nature. For example, in addition to its symbolic value and appeal, a national language has other roles in the process, including: (a) becoming the primary medium of communication which permits the nation to function efficiently in its political and economic life, (b) promoting social cohesion, allowing the nation to develop a common culture, and (c) forming a primordial basis for self-determination. Moreover, because of its cross-cutting nature, language interventions are rarely isolated activities. Languages are adopted by speakers, taking root in and spreading between communities because they are legitimated by legislation, and then reproduced through institutions like the education and military systems. Pádraig Ó’ Riagáin (1997) makes a case for this observing that “Language policy is formulated, implemented, and accomplishes its results within a complex interrelated set of economic, social, and political processes which include, inter alia, the operation of other non-language state policies” (p. 45). In the Turkish case, its foundational role in the formation of the Turkish nation-state but its linkages to human rights issues raises interesting issues about how socio-cultural practices become reproduced through institutional infrastructure formation. This dissertation is a country-level case study looking at Turkey’s nation-state building process through the lens of its language and education policy development processes with a focus on the early years of the Republic between 1927 and 1970. This project examines how different groups self-identified or were self-identified (as the case may be) in official Turkish statistical publications (e.g., the Turkish annual statistical yearbooks and the population censuses) during that time period when language and ethnicity data was made publicly available. The overarching questions this dissertation explores include: 1.What were the geo-political conditions surrounding the development and influencing the Turkish government’s language and education policies? 2.Are there any observable patterns in the geo-spatial distribution of language, literacy, and education participation rates over time? In what ways, are these traditionally linked variables (language, literacy, education participation) problematic? 3.What do changes in population identifiers, e.g., language and ethnicity, suggest about the government’s approach towards nation-state building through the construction of a civic Turkish identity and institution building? Archival secondary source data was digitized, aggregated by categories relevant to this project at national and provincial levels and over the course of time (primarily between 1927 and 2000). The data was then re-aggregated into values that could be longitudinally compared and then layered on aspatial administrative maps. This dissertation contributes to existing body of social policy literature by taking an interdisciplinary approach in looking at the larger socio-economic contexts in which language and education policies are produced.
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The Exhibitium Project , awarded by the BBVA Foundation, is a data-driven project developed by an international consortium of research groups . One of its main objectives is to build a prototype that will serve as a base to produce a platform for the recording and exploitation of data about art-exhibitions available on the Internet . Therefore, our proposal aims to expose the methods, procedures and decision-making processes that have governed the technological implementation of this prototype, especially with regard to the reuse of WordPress (WP) as development framework.
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High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.
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Below cloud scavenging processes have been investigated considering a numerical simulation, local atmospheric conditions and particulate matter (PM) concentrations, at different sites in Germany. The below cloud scavenging model has been coupled with bulk particulate matter counter TSI (Trust Portacounter dataset, consisting of the variability prediction of the particulate air concentrations during chosen rain events. The TSI samples and meteorological parameters were obtained during three winter Campaigns: at Deuselbach, March 1994, consisting in three different events; Sylt, April 1994 and; Freiburg, March 1995. The results show a good agreement between modeled and observed air concentrations, emphasizing the quality of the conceptual model used in the below cloud scavenging numerical modeling. The results between modeled and observed data have also presented high square Pearson coefficient correlations over 0.7 and significant, except the Freiburg Campaign event. The differences between numerical simulations and observed dataset are explained by the wind direction changes and, perhaps, the absence of advection mass terms inside the modeling. These results validate previous works based on the same conceptual model.
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Geographic Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis, and the literature proposes several conceptual and logical data models for GDW. However, little effort has been focused on studying how spatial data redundancy affects SOLAP (Spatial On-Line Analytical Processing) query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. We also analyze the issue of indexing, aiming at improving SOLAP query performance on a redundant GDW. Comparisons of the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicate that the SB-index significantly improves the elapsed time in query processing from 25% up to 99% with regard to SOLAP queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. We also investigate the impact of the increase in data volume on the performance. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Performance tests also show that the SB-index is far more compact than the star-join, requiring only a small fraction of at most 0.20% of the volume. Moreover, we propose a specific enhancement of the SB-index to deal with spatial data redundancy. This enhancement improved performance from 80 to 91% for redundant GDW schemas.