989 resultados para Log steaming


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This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed.

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The Michigan Basin is located in the upper Midwest region of the United States and is centered geographically over the Lower Peninsula of Michigan. It is filled primarily with Paleozoic carbonates and clastics, overlying Precambrian basement rocks and covered by Pleistocene glacial drift. In Michigan, more than 46,000 wells have been drilled in the basin, many producing significant quantities of oil and gas since the 1920s in addition to providing a wealth of data for subsurface visualization. Well log tomography, formerly log-curve amplitude slicing, is a visualization method recently developed at Michigan Technological University to correlate subsurface data by utilizing the high vertical resolution of well log curves. The well log tomography method was first successfully applied to the Middle Devonian Traverse Group within the Michigan Basin using gamma ray log curves. The purpose of this study is to prepare a digital data set for the Middle Devonian Dundee and Rogers City Limestones, apply the well log tomography method to this data and from this application, interpret paleogeographic trends in the natural radioactivity. Both the Dundee and Rogers City intervals directly underlie the Traverse Group and combined are the most prolific reservoir within the Michigan Basin. Differences between this study and the Traverse Group include increased well control and “slicing” of a more uniform lithology. Gamma ray log curves for the Dundee and Rogers City Limestones were obtained from 295 vertical wells distributed over the Lower Peninsula of Michigan, converted to Log ASCII Standard files, and input into the well log tomography program. The “slicing” contour results indicate that during the formation of the Dundee and Rogers City intervals, carbonates and evaporites with low natural radioactive signatures on gamma ray logs were deposited. This contrasts the higher gamma ray amplitudes from siliciclastic deltas that cyclically entered the basin during Traverse Group deposition. Additionally, a subtle north-south, low natural radioactive trend in the center of the basin may correlate with previously published Dundee facies tracts. Prominent trends associated with the distribution of limestone and dolomite are not observed because the regional range of gamma ray values for both carbonates are equivalent in the Michigan Basin and additional log curves are needed to separate these lithologies.

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This work is conducted to study the complications associated with the sonic log prediction in carbonate logs and to investigate the possible solutions to accurately predict the sonic logs in Traverse Limestone. Well logs from fifty different wells were analyzed to define the mineralogy of the Traverse Limestone by using conventional 4-mineral and 3-mineral identification approaches. We modified the conventional 3-mineral identification approach (that completely neglects the gamma ray response) to correct the shale effects on the basis of gamma ray log before employing the 3-mineral identification. This modification helped to get the meaningful insight of the data when a plot was made between DGA (dry grain density) and UMA (Photoelectric Volumetric Cross-section) with the characteristic ternary diagram of the quartz, calcite and dolomite. The results were then compared with the 4-mineral identification approach. Contour maps of the average mineral fractions present in the Traverse Limestone were prepared to see the basin wide mineralogy of Traverse Limestone. In the second part, sonic response of Traverse Limestone was predicted in fifty randomly distributed wells. We used the modified time average equation that accounts for the shale effects on the basis of gamma ray log, and used it to predict the sonic behavior from density porosity and average porosity. To account for the secondary porosity of dolomite, we subtracted the dolomitic fraction of clean porosity from the total porosity. The pseudo-sonic logs were then compared with the measured sonic logs on the root mean square (RMS) basis. Addition of dolomite correction in modified time average equation improved the results of sonic prediction from neutron porosity and average porosity. The results demonstrated that sonic logs could be predicted in carbonate rocks with a root mean square error of about 4μsec/ft. We also attempted the use of individual mineral components for sonic log prediction but the ambiguities in mineral fractions and in the sonic properties of the minerals limited the accuracy of the results.

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As more and more open-source software components become available on the internet we need automatic ways to label and compare them. For example, a developer who searches for reusable software must be able to quickly gain an understanding of retrieved components. This understanding cannot be gained at the level of source code due to the semantic gap between source code and the domain model. In this paper we present a lexical approach that uses the log-likelihood ratios of word frequencies to automatically provide labels for software components. We present a prototype implementation of our labeling/comparison algorithm and provide examples of its application. In particular, we apply the approach to detect trends in the evolution of a software system.

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OBJECTIVE: To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines. DESIGN: We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day. MEASUREMENTS: We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies. RESULTS: The size of the result sets from a sample of queries showed a bimodal distribution, with peaks at approximately 3 and 100 results, suggesting that a large group of queries was tightly focused and another was broad. Like Web search engine sessions, most PubMed sessions consisted of a single query. However, PubMed queries contained more terms. CONCLUSION: PubMed's usage profile should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.

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by A. Goldfaden. For violin arr. by Herman Fiedler