992 resultados para Database application


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A database of representative BRDF and BPDF derived from the POLDER measurements. From the huge amount of data acquired by the spaceborne instrument over a period of 7 years, we selected a set of targets with high quality observations. The selection aimed at a large number of observations, free of cloud or aerosol contamination, acquired in diverse observation geometry with a focus on the backscatter direction that shows the specific Hot-Spot signature. The targets are sorted according to the 16-classes IGBP land cover classification system and the target selection aims at a spatial representativeness within the class. The database thus provides a set of high quality BRDF and BPDF samples that can be used to assess the typical variability of natural surface reflectances or to evaluate models.

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A uniform chronology for foraminifera-based sea surface temperature records has been established in more than 120 sediment cores obtained from the equatorial and eastern Atlantic up to the Arctic Ocean. The chronostratigraphy of the last 30,000 years is mainly based on published d18O records and 14C ages from accelerator mass spectrometry, converted into calendar-year ages. The high-precision age control provides the database necessary for the uniform reconstruction of the climate interval of the Last Glacial Maximum within the GLAMAP-2000 project.

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This project is about retrieving data in range without allowing the server to read it, when the database is stored in the server. Basically, our goal is to build a database that allows the client to maintain the confidentiality of the data stored, despite all the data is stored in a different location from the client's hard disk. This means that all the information written on the hard disk can be easily read by another person who can do anything with it. Given that, we need to encrypt that data from eavesdroppers or other people. This is because they could sell it or log into accounts and use them for stealing money or identities. In order to achieve this, we need to encrypt the data stored in the hard drive, so that only the possessor of the key can easily read the information stored, while all the others are going to read only encrypted data. Obviously, according to that, all the data management must be done by the client, otherwise any malicious person can easily retrieve it and use it for any malicious intention. All the methods analysed here relies on encrypting data in transit. In the end of this project we analyse 2 theoretical and practical methods for the creation of the above databases and then we tests them with 3 datasets and with 10, 100 and 1000 queries. The scope of this work is to retrieve a trend that can be useful for future works based on this project.

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In this study we review a global set of alkenone- and foraminiferal Mg/Ca-derived sea surface temperatures (SST) records from the Holocene and compare them with a suite of published Eemian SST records based on the same approach. For the Holocene, the alkenone SST records belong to the actualized GHOST database (Kim, J.-H., Schneider R.R., 2004). The actualized GHOST database not only confirms the SST changes previously described but also documents the Holocene temperature evolution in new oceanic regions such as the Northwestern Atlantic, the eastern equatorial Pacific, and the Southern Ocean. A comparison of Holocene SST records stemming from the two commonly applied paleothermometry methods reveals contrasting - sometimes divergent - SST evolution, particularly at low latitudes where SST records are abundant enough to infer systematic discrepancies at a regional scale. Opposite SST trends at particular locations could be explained by out-of-phase trends in seasonal insolation during the Holocene. This hypothesis assumes that a strong contrast in the ecological responses of coccolithophores and planktonic foraminifera to winter and summer oceanographic conditions is the ultimate reason for seasonal differences in the origin of the temperature signal provided by these organisms. As a simple test for this hypothesis, Eemian SST records are considered because the Holocene and Eemian time periods experienced comparable changes in orbital configurations, but had a higher magnitude in insolation variance during the Eemian. For several regions, SST changes during both interglacials were of a similar sign, but with higher magnitudes during the Eemian as compared to the Holocene. This observation suggests that the ecological mechanism shaping SST trends during the Holocene was comparable during the penultimate interglacial period. Although this "ecology hypothesis" fails to explain all of the available results, we argue that any other mechanism would fail to satisfactorily explain the observed SST discrepancies among proxies.

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Two years of harmonized aerosol number size distribution data from 24 European field monitoring sites have been analysed. The results give a comprehensive overview of the European near surface aerosol particle number concentrations and number size distributions between 30 and 500 nm of dry particle diameter. Spatial and temporal distribution of aerosols in the particle sizes most important for climate applications are presented. We also analyse the annual, weekly and diurnal cycles of the aerosol number concentrations, provide log-normal fitting parameters for median number size distributions, and give guidance notes for data users. Emphasis is placed on the usability of results within the aerosol modelling community. We also show that the aerosol number concentrations of Aitken and accumulation mode particles (with 100 nm dry diameter as a cut-off between modes) are related, although there is significant variation in the ratios of the modal number concentrations. Different aerosol and station types are distinguished from this data and this methodology has potential for further categorization of stations aerosol number size distribution types. The European submicron aerosol was divided into characteristic types: Central European aerosol, characterized by single mode median size distributions, unimodal number concentration histograms and low variability in CCN-sized aerosol number concentrations; Nordic aerosol with low number concentrations, although showing pronounced seasonal variation of especially Aitken mode particles; Mountain sites (altitude over 1000 m a.s.l.) with a strong seasonal cycle in aerosol number concentrations, high variability, and very low median number concentrations. Southern and Western European regions had fewer stations, which decreases the regional coverage of these results. Aerosol number concentrations over the Britain and Ireland had very high variance and there are indications of mixed air masses from several source regions; the Mediterranean aerosol exhibit high seasonality, and a strong accumulation mode in the summer. The greatest concentrations were observed at the Ispra station in Northern Italy with high accumulation mode number concentrations in the winter. The aerosol number concentrations at the Arctic station Zeppelin in Ny-Ålesund in Svalbard have also a strong seasonal cycle, with greater concentrations of accumulation mode particles in winter, and dominating summer Aitken mode indicating more recently formed particles. Observed particles did not show any statistically significant regional work-week or weekday related variation in number concentrations studied. Analysis products are made for open-access to the research community, available in a freely accessible internet site. The results give to the modelling community a reliable, easy-to-use and freely available comparison dataset of aerosol size distributions.

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Modern software applications are becoming more dependent on database management systems (DBMSs). DBMSs are usually used as black boxes by software developers. For example, Object-Relational Mapping (ORM) is one of the most popular database abstraction approaches that developers use nowadays. Using ORM, objects in Object-Oriented languages are mapped to records in the database, and object manipulations are automatically translated to SQL queries. As a result of such conceptual abstraction, developers do not need deep knowledge of databases; however, all too often this abstraction leads to inefficient and incorrect database access code. Thus, this thesis proposes a series of approaches to improve the performance of database-centric software applications that are implemented using ORM. Our approaches focus on troubleshooting and detecting inefficient (i.e., performance problems) database accesses in the source code, and we rank the detected problems based on their severity. We first conduct an empirical study on the maintenance of ORM code in both open source and industrial applications. We find that ORM performance-related configurations are rarely tuned in practice, and there is a need for tools that can help improve/tune the performance of ORM-based applications. Thus, we propose approaches along two dimensions to help developers improve the performance of ORM-based applications: 1) helping developers write more performant ORM code; and 2) helping developers configure ORM configurations. To provide tooling support to developers, we first propose static analysis approaches to detect performance anti-patterns in the source code. We automatically rank the detected anti-pattern instances according to their performance impacts. Our study finds that by resolving the detected anti-patterns, the application performance can be improved by 34% on average. We then discuss our experience and lessons learned when integrating our anti-pattern detection tool into industrial practice. We hope our experience can help improve the industrial adoption of future research tools. However, as static analysis approaches are prone to false positives and lack runtime information, we also propose dynamic analysis approaches to further help developers improve the performance of their database access code. We propose automated approaches to detect redundant data access anti-patterns in the database access code, and our study finds that resolving such redundant data access anti-patterns can improve application performance by an average of 17%. Finally, we propose an automated approach to tune performance-related ORM configurations using both static and dynamic analysis. Our study shows that our approach can help improve application throughput by 27--138%. Through our case studies on real-world applications, we show that all of our proposed approaches can provide valuable support to developers and help improve application performance significantly.

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This paper discusses the advantages of database-backed websites and describes the model for a library website implemented at the University of Nottingham using open source software, PHP and MySQL. As websites continue to grow in size and complexity it becomes increasingly important to introduce automation to help manage them. It is suggested that a database-backed website offers many advantages over one built from static HTML pages. These include a consistency of style and content, the ability to present different views of the same data, devolved editing and enhanced security. The University of Nottingham Library Services website is described and issues surrounding its design, technological implementation and management are explored.

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Homomorphic encryption is a particular type of encryption method that enables computing over encrypted data. This has a wide range of real world ramifications such as being able to blindly compute a search result sent to a remote server without revealing its content. In the first part of this thesis, we discuss how database search queries can be made secure using a homomorphic encryption scheme based on the ideas of Gahi et al. Gahi’s method is based on the integer-based fully homomorphic encryption scheme proposed by Dijk et al. We propose a new database search scheme called the Homomorphic Query Processing Scheme, which can be used with the ring-based fully homomorphic encryption scheme proposed by Braserski. In the second part of this thesis, we discuss the cybersecurity of the smart electric grid. Specifically, we use the Homomorphic Query Processing scheme to construct a keyword search technique in the smart grid. Our work is based on the Public Key Encryption with Keyword Search (PEKS) method introduced by Boneh et al. and a Multi-Key Homomorphic Encryption scheme proposed by L´opez-Alt et al. A summary of the results of this thesis (specifically the Homomorphic Query Processing Scheme) is published at the 14th Canadian Workshop on Information Theory (CWIT).

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One way to do a bibliometric study is to examine each of the records that make up a database, each record and extract key areas that may disclose relevant information about the use of the database and documents in the collection . This article shows how a reference database allows to obtain important data that can reach conclusions that in some cases surprising. For this study we used the following fields of Database Control Documentary Indigenous Nationalities of Costa Rica 1979-2003: author, place of publication, publisher, year, language and support. The database analyzed has two thousand records and was developed in the Winisis. Moreover, analysis of documents was made after processing of the data, which was to export records to Excel software Winisis. After this information extracted from their chosen fields and are held by their respective separate chart or graph to present the results obtained. Furthermore, we show the application of different methods to learn more about the scientific aspects as: the Price Index, the Index of Collaboration This contribution will, first, for (as) students in the course of the race Metric Studies of Library and Information Science, National University, demonstrate and practice what you learned in this area. They may also benefit the (as) professionals from different areas, such as anthropologists (as), sociologists (as), linguists and librarians (as), among others (as).

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Five years of SMOS L-band brightness temperature data intercepting a large number of tropical cyclones (TCs) are analyzed. The storm-induced half-power radio-brightness contrast (ΔI) is defined as the difference between the brightness observed at a specific wind force and that for a smooth water surface with the same physical parameters. ΔI can be related to surface wind speed and has been estimated for ~ 300 TCs that intercept with SMOS measurements. ΔI, expressed in a common storm-centric coordinate system, shows that mean brightness contrast monotonically increases with increased storm intensity ranging from ~ 5 K for strong storms to ~ 24 K for the most intense Category 5 TCs. A remarkable feature of the 2D mean ΔI fields and their variability is that maxima are systematically found on the right quadrants of the storms in the storm-centered coordinate frame, consistent with the reported asymmetric structure of the wind and wave fields in hurricanes. These results highlight the strong potential of SMOS measurements to improve monitoring of TC intensification and evolution. An improved empirical geophysical model function (GMF) was derived using a large ensemble of co-located SMOS ΔI, aircraft and H*WIND (a multi-measurement analysis) surface wind speed data. The GMF reveals a quadratic relationship between ΔI and the surface wind speed at a height of 10 m (U10). ECMWF and NCEP analysis products and SMOS derived wind speed estimates are compared to a large ensemble of H*WIND 2D fields. This analysis confirms that the surface wind speed in TCs can effectively be retrieved from SMOS data with an RMS error on the order of 10 kt up to 100 kt. SMOS wind speed products above hurricane force (64 kt) are found to be more accurate than those derived from NWP analyses products that systematically underestimate the surface wind speed in these extreme conditions. Using co-located estimates of rain rate, we show that the L-band radio-brightness contrasts could be weakly affected by rain or ice-phase clouds and further work is required to refine the GMF in this context.

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A comprehensive database of temperature, salinity and bio-chemical parameters in the Mediterranean and Black Sea has been constructed through comprehensive co-operation between the bordering countries. Statistical climatologies have been computed with all assembled and quality controlled data. The database, designed to initiate and validate prediction models, also represents a system to quality-check new incoming data produced by ocean observing systems.

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Replication of eukaryotic chromosomes initiates at multiple sites called replication origins. Replication origins are best understood in the budding yeast Saccharomyces cerevisiae, where several complementary studies have mapped their locations genome-wide. We have collated these datasets, taking account of the resolution of each study, to generate a single list of distinct origin sites. OriDB provides a web-based catalogue of these confirmed and predicted S.cerevisiae DNA replication origin sites. Each proposed or confirmed origin site appears as a record in OriDB, with each record comprising seven pages. These pages provide, in text and graphical formats, the following information: genomic location and chromosome context of the origin site; time of origin replication; DNA sequence of proposed or experimentally confirmed origin elements; free energy required to open the DNA duplex (stress-induced DNA duplex destabilization or SIDD); and phylogenetic conservation of sequence elements. In addition, OriDB encourages community submission of additional information for each origin site through a User Notes facility. Origin sites are linked to several external resources, including the Saccharomyces Genome Database (SGD) and relevant publications at PubMed. Finally, a Chromosome Viewer utility allows users to interactively generate graphical representations of DNA replication data genome-wide. OriDB is available at www.oridb.org.

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Thesis (Ph.D, Computing) -- Queen's University, 2016-09-30 09:55:51.506

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Twitter is a highly popular social media which on one hand allows information transmission in real time and on the other hand represents a source of open access homogeneous text data. We propose an analysis of the most common self-reported COVID symptoms from a dataset of Italian tweets to investigate the evolution of the pandemic in Italy from the end of September 2020 to the end of January 2021. After manually filtering tweets actually describing COVID symptoms from the database - which contains words related to fever, cough and sore throat - we discuss usefulness of such filtering. We then compare our time series with the daily data of new hospitalisations in Italy, with the aim of building a simple linear regression model that accounts for the delay which is observed from the tweets mentioning individual symptoms to new hospitalisations. We discuss both the results and limitations of linear regression given that our data suggests that the relationship between time series of symptoms tweets and of new hospitalisations changes towards the end of the acquisition.