28 resultados para Hay, John, 1838-1905.


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http://www.archive.org/details/johnludwigkrapfe00kretiala

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http://www.archive.org/details/historyofcatholi00sheaiala

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http://www.archive.org/details/jamesevans00maclrich

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http://www.archive.org/details/womeninthemissio00telfuoft

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http://www.archive.org/details/johnwesleytheman00pikeuoft

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http://www.archive.org/details/bibleillustratio00ingluoft

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Throughout the history of the Church, the Epistle to the Hebrews has been one of the most puzzling letters in the Canon, particularly regarding the implications of understanding the person of Jesus Christ. John Chrysostom, an important patristic writer, is acknowledged to have made significant contributions to the exegesis of this letter. Chrysostom's thought became the norm for traditional thinking and interpretation of this letter in the Middle Ages. Martin Luther's reception of Chrysostom's Homilies on Hebrews presents a unique interpretation that some scholars may describe as the "Reformation Discovery" on Hebrews. In tracing Luther's reception and appropriation of Chrysostom's exegesis of the letter to the Hebrews, there is a noticeable and significant shift in Christological interpretation. Whether or not these modifications were necessary is a matter of debate; however, they do reflect Luther's contextual and existential questions regarding faith, Christ and knowledge of God, which is evident in his Lectures on Hebrews.

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A listing of graduate of Boston University School of Theology and predecessor school. Arranged by class year, alphabetical by last name and geographically by region.

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The data streaming model provides an attractive framework for one-pass summarization of massive data sets at a single observation point. However, in an environment where multiple data streams arrive at a set of distributed observation points, sketches must be computed remotely and then must be aggregated through a hierarchy before queries may be conducted. As a result, many sketch-based methods for the single stream case do not apply directly, as either the error introduced becomes large, or because the methods assume that the streams are non-overlapping. These limitations hinder the application of these techniques to practical problems in network traffic monitoring and aggregation in sensor networks. To address this, we develop a general framework for evaluating and enabling robust computation of duplicate-sensitive aggregate functions (e.g., SUM and QUANTILE), over data produced by distributed sources. We instantiate our approach by augmenting the Count-Min and Quantile-Digest sketches to apply in this distributed setting, and analyze their performance. We conclude with experimental evaluation to validate our analysis.