26 resultados para Cabot, John, -1498?


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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 well-known paradigm for load balancing in distributed systems is the``power of two choices,''whereby an item is stored at the less loaded of two (or more) random alternative servers. We investigate the power of two choices in natural settings for distributed computing where items and servers reside in a geometric space and each item is associated with the server that is its nearest neighbor. This is in fact the backdrop for distributed hash tables such as Chord, where the geometric space is determined by clockwise distance on a one-dimensional ring. Theoretically, we consider the following load balancing problem. Suppose that servers are initially hashed uniformly at random to points in the space. Sequentially, each item then considers d candidate insertion points also chosen uniformly at random from the space,and selects the insertion point whose associated server has the least load. For the one-dimensional ring, and for Euclidean distance on the two-dimensional torus, we demonstrate that when n data items are hashed to n servers,the maximum load at any server is log log n / log d + O(1) with high probability. While our results match the well-known bounds in the standard setting in which each server is selected equiprobably, our applications do not have this feature, since the sizes of the nearest-neighbor regions around servers are non-uniform. Therefore, the novelty in our methods lies in developing appropriate tail bounds on the distribution of nearest-neighbor region sizes and in adapting previous arguments to this more general setting. In addition, we provide simulation results demonstrating the load balance that results as the system size scales into the millions.