864 resultados para Data mining methods
Resumo:
En este artículo se propone el análisis de las interacciones entre usuarios de Twitter, tanto lo que se genera alrededor de un usuario concreto como el análisis de un hashtag dado durante un periodo de tiempo establecido.
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Past and current climate change has already induced drastic biological changes. We need projections of how future climate change will further impact biological systems. Modeling is one approach to forecast future ecological impacts, but requires data for model parameterization. As collecting new data is costly, an alternative is to use the increasingly available georeferenced species occurrence and natural history databases. Here, we illustrate the use of such databases to assess climate change impacts on mountain flora. We show that these data can be used effectively to derive dynamic impact scenarios, suggesting upward migration of many species and possible extinctions when no suitable habitat is available at higher elevations. Systematically georeferencing all existing natural history collections data in mountain regions could allow a larger assessment of climate change impact on mountain ecosystems in Europe and elsewhere.
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Many states are striving to keep their deer population to a sustainable and controllable level while maximizing public safety. In Iowa, measures to control the deer population include annual deer hunts and special deer herd management plans in urban areas. While these plans may reduce the deer population, traffic safety in these areas has not been fully assessed. Using deer population data from the Iowa Department of Natural Resources and data on deer-vehicle crashes and deer carcass removals from the Iowa Department of Transportation, the authors examined the relationship between deer-vehicle collisions, deer density, and land use in three urban areas in Iowa that have deer management plans in place (Cedar Rapids, Dubuque, and Iowa City) over the period 2002 to 2007. First, a comparison of deer-vehicle crash counts and deer carcass removal counts was conducted at the county level. Further, the authors estimated econometric models to investigate the factors that influence the frequency and severity of deer-vehicle crashes in these zones. Overall, the number of deer carcasses removed on the primary roads in these counties was greater than the number of reported deervehicle crashes on those roads. These differences can be attributed to a number of reasons, including variability in data reporting and data collection practices. In addition, high rates of underreporting of crashes were found on major routes that carry high volumes of traffic. This study also showed that multiple factors affect deer-vehicle crashes and corresponding injury outcomes in urban management zones. The identified roadway and non-roadway factors could be useful for identifying locations on the transportation system that significantly impact deer species and safety and for determining appropriate countermeasures for mitigation. Efforts to reduce deer density adjacent to roads and developed land and to provide wider shoulders on undivided roads are recommended. Improving the consistency and accuracy of deer carcass and deer-vehicle collision data collection methods and practices is also desirable.
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El objetivo de este artículo es introducir al lector español en algunos debates recientes de la comunidad de humanistas digitales de habla inglesa. En lugar de intentar definir la disciplina en términos absolutos, se ha optado por una aproximación diacrónica aunque se ha puesto el acento en algunos principios como la interdisciplinariedad y la construcción de modelos, valores como el acceso y el código abierto, y prácticas como la minería de datos y la colaboración.
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Aquesta exposició vol presentar breument el ventall d'eines disponibles, la terminologia utilitzada i, en general, el marc metodològic de l'estadística exploratoria i de l'analisi de dades, el paradigma de la disciplina.En el decurs dels darrers anys, la disciplina no ha estat pas capgirada, però de tota manera sí que cal una actualització permanent.S'han forjat i provat algunes eines gairebé només esbossades, han aparegut nous dominis d'aplicació. Cal precisar la relació amb els competidors i dinamics veïns (intel·ligencia artificial, xarxes neurals, Data Mining). La perspectiva que presento dels mètodes d'anàlisi de dades emana evidentment d'un punt de vista particular; altres punts de vista poden ser igualment vàlids
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Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.
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The European Space Agency's Gaia mission will create the largest and most precise three dimensional chart of our galaxy (the Milky Way), by providing unprecedented position, parallax, proper motion, and radial velocity measurements for about one billion stars. The resulting catalogue will be made available to the scientific community and will be analyzed in many different ways, including the production of a variety of statistics. The latter will often entail the generation of multidimensional histograms and hypercubes as part of the precomputed statistics for each data release, or for scientific analysis involving either the final data products or the raw data coming from the satellite instruments. In this paper we present and analyze a generic framework that allows the hypercube generation to be easily done within a MapReduce infrastructure, providing all the advantages of the new Big Data analysis paradigmbut without dealing with any specific interface to the lower level distributed system implementation (Hadoop). Furthermore, we show how executing the framework for different data storage model configurations (i.e. row or column oriented) and compression techniques can considerably improve the response time of this type of workload for the currently available simulated data of the mission. In addition, we put forward the advantages and shortcomings of the deployment of the framework on a public cloud provider, benchmark against other popular solutions available (that are not always the best for such ad-hoc applications), and describe some user experiences with the framework, which was employed for a number of dedicated astronomical data analysis techniques workshops.
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Land plants have had the reputation of being problematic for DNA barcoding for two general reasons: (i) the standard DNA regions used in algae, animals and fungi have exceedingly low levels of variability and (ii) the typically used land plant plastid phylogenetic markers (e.g. rbcL, trnL-F, etc.) appear to have too little variation. However, no one has assessed how well current phylogenetic resources might work in the context of identification (versus phylogeny reconstruction). In this paper, we make such an assessment, particularly with two of the markers commonly sequenced in land plant phylogenetic studies, plastid rbcL and internal transcribed spacers of the large subunits of nuclear ribosomal DNA (ITS), and find that both of these DNA regions perform well even though the data currently available in GenBank/EBI were not produced to be used as barcodes and BLAST searches are not an ideal tool for this purpose. These results bode well for the use of even more variable regions of plastid DNA (such as, for example, psbA-trnH) as barcodes, once they have been widely sequenced. In the short term, efforts to bring land plant barcoding up to the standards being used now in other organisms should make swift progress. There are two categories of DNA barcode users, scientists in fields other than taxonomy and taxonomists. For the former, the use of mitochondrial and plastid DNA, the two most easily assessed genomes, is at least in the short term a useful tool that permits them to get on with their studies, which depend on knowing roughly which species or species groups they are dealing with, but these same DNA regions have important drawbacks for use in taxonomic studies (i.e. studies designed to elucidate species limits). For these purposes, DNA markers from uniparentally (usually maternally) inherited genomes can only provide half of the story required to improve taxonomic standards being used in DNA barcoding. In the long term, we will need to develop more sophisticated barcoding tools, which would be multiple, low-copy nuclear markers with sufficient genetic variability and PCR-reliability; these would permit the detection of hybrids and permit researchers to identify the 'genetic gaps' that are useful in assessing species limits.
Resumo:
The European Space Agency's Gaia mission will create the largest and most precise three dimensional chart of our galaxy (the Milky Way), by providing unprecedented position, parallax, proper motion, and radial velocity measurements for about one billion stars. The resulting catalogue will be made available to the scientific community and will be analyzed in many different ways, including the production of a variety of statistics. The latter will often entail the generation of multidimensional histograms and hypercubes as part of the precomputed statistics for each data release, or for scientific analysis involving either the final data products or the raw data coming from the satellite instruments. In this paper we present and analyze a generic framework that allows the hypercube generation to be easily done within a MapReduce infrastructure, providing all the advantages of the new Big Data analysis paradigmbut without dealing with any specific interface to the lower level distributed system implementation (Hadoop). Furthermore, we show how executing the framework for different data storage model configurations (i.e. row or column oriented) and compression techniques can considerably improve the response time of this type of workload for the currently available simulated data of the mission. In addition, we put forward the advantages and shortcomings of the deployment of the framework on a public cloud provider, benchmark against other popular solutions available (that are not always the best for such ad-hoc applications), and describe some user experiences with the framework, which was employed for a number of dedicated astronomical data analysis techniques workshops.
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BACKGROUND: PCR has the potential to detect and precisely quantify specific DNA sequences, but it is not yet often used as a fully quantitative method. A number of data collection and processing strategies have been described for the implementation of quantitative PCR. However, they can be experimentally cumbersome, their relative performances have not been evaluated systematically, and they often remain poorly validated statistically and/or experimentally. In this study, we evaluated the performance of known methods, and compared them with newly developed data processing strategies in terms of resolution, precision and robustness. RESULTS: Our results indicate that simple methods that do not rely on the estimation of the efficiency of the PCR amplification may provide reproducible and sensitive data, but that they do not quantify DNA with precision. Other evaluated methods based on sigmoidal or exponential curve fitting were generally of both poor resolution and precision. A statistical analysis of the parameters that influence efficiency indicated that it depends mostly on the selected amplicon and to a lesser extent on the particular biological sample analyzed. Thus, we devised various strategies based on individual or averaged efficiency values, which were used to assess the regulated expression of several genes in response to a growth factor. CONCLUSION: Overall, qPCR data analysis methods differ significantly in their performance, and this analysis identifies methods that provide DNA quantification estimates of high precision, robustness and reliability. These methods allow reliable estimations of relative expression ratio of two-fold or higher, and our analysis provides an estimation of the number of biological samples that have to be analyzed to achieve a given precision.
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This report is concerned with the prediction of the long-time creep and shrinkage behavior of concrete. It is divided into three main areas. l. The development of general prediction methods that can be used by a design engineer when specific experimental data are not available. 2. The development of prediction methods based on experimental data. These methods take advantage of equations developed in item l, and can be used to accurately predict creep and shrinkage after only 28 days of data collection. 3. Experimental verification of items l and 2, and the development of specific prediction equations for four sand-lightweight aggregate concretes tested in the experimental program. The general prediction equations and methods are developed in Chapter II. Standard Equations to estimate the creep of normal weight concrete (Eq. 9), sand-lightweight concrete (Eq. 12), and lightweight concrete (Eq. 15) are recommended. These equations are developed for standard conditions (see Sec. 2. 1) and correction factors required to convert creep coefficients obtained from equations 9, 12, and 15 to valid predictions for other conditions are given in Equations 17 through 23. The correction factors are shown graphically in Figs. 6 through 13. Similar equations and methods are developed for the prediction of the shrinkage of moist cured normal weight concrete (Eq. 30}, moist cured sand-lightweight concrete (Eq. 33}, and moist cured lightweight concrete (Eq. 36). For steam cured concrete the equations are Eq. 42 for normal weight concrete, and Eq. 45 for lightweight concrete. Correction factors are given in Equations 47 through 52 and Figs., 18 through 24. Chapter III summarizes and illustrates, by examples, the prediction methods developed in Chapter II. Chapters IV and V describe an experimental program in which specific prediction equations are developed for concretes made with Haydite manufactured by Hydraulic Press Brick Co. (Eqs. 53 and 54}, Haydite manufactured by Buildex Inc. (Eqs. 55 and 56), Haydite manufactured by The Cater-Waters Corp. (Eqs. 57 and 58}, and Idealite manufactured by Idealite Co. (Eqs. 59 and 60). General prediction equations are also developed from the data obtained in the experimental program (Eqs. 61 and 62) and are compared to similar equations developed in Chapter II. Creep and Shrinkage prediction methods based on 28 day experimental data are developed in Chapter VI. The methods are verified by comparing predicted and measured values of the long-time creep and shrinkage of specimens tested at the University of Iowa (see Chapters IV and V) and elsewhere. The accuracy obtained is shown to be superior to other similar methods available to the design engineer.
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In recent years, studies into the reasons for dropping out of higher education (including online education) have been undertaken with greater regularity, parallel to the rise in the relative weight of this type of education, compared with brick-and-mortar education. However, the work invested in characterising the students who drop out of education, compared with those who do not, appears not to have had the same relevance as that invested in the analysis of the causes. The definition of dropping out is very sensitive to the context. In this article, we reach a purely empirical definition of student dropping out, based on the probability of not continuing a specific academic programme following several consecutive semesters of "theoretical break". Dropping out should be properly defined before analysing its causes, as well as comparing the drop-out rates between the different online programmes, or between online and on-campus ones. Our results show that there are significant differences among programmes, depending on their theoretical extension, but not their domain of knowledge.
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BACKGROUND: Several European HIV observational data bases have, over the last decade, accumulated a substantial number of resistance test results and developed large sample repositories, There is a need to link these efforts together, We here describe the development of such a novel tool that allows to bind these data bases together in a distributed fashion for which the control and data remains with the cohorts rather than classic data mergers.METHODS: As proof-of-concept we entered two basic queries into the tool: available resistance tests and available samples. We asked for patients still alive after 1998-01-01, and between 180 and 195 cm of height, and how many samples or resistance tests there would be available for these patients, The queries were uploaded with the tool to a central web server from which each participating cohort downloaded the queries with the tool and ran them against their database, The numbers gathered were then submitted back to the server and we could accumulate the number of available samples and resistance tests.RESULTS: We obtained the following results from the cohorts on available samples/resistance test: EuResist: not availableI11,194; EuroSIDA: 20,71611,992; ICONA: 3,751/500; Rega: 302/302; SHCS: 53,78311,485, In total, 78,552 samples and 15,473 resistance tests were available amongst these five cohorts. Once these data items have been identified, it is trivial to generate lists of relevant samples that would be usefuI for ultra deep sequencing in addition to the already available resistance tests, Saon the tool will include small analysis packages that allow each cohort to pull a report on their cohort profile and also survey emerging resistance trends in their own cohort,CONCLUSIONS: We plan on providing this tool to all cohorts within the Collaborative HIV and Anti-HIV Drug Resistance Network (CHAIN) and will provide the tool free of charge to others for any non-commercial use, The potential of this tool is to ease collaborations, that is, in projects requiring data to speed up identification of novel resistance mutations by increasing the number of observations across multiple cohorts instead of awaiting single cohorts or studies to reach the critical number needed to address such issues.
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DDM is a framework that combines intelligent agents and artificial intelligence traditional algorithms such as classifiers. The central idea of this project is to create a multi-agent system that allows to compare different views into a single one.