10 resultados para Leconte de Lisle, 1818-1894
em Boston University Digital Common
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Handwritten letter from Timothy Merritt to sister (?) Ruth Merritt regarding her loss of religious conviction. Dated Nov. 10, 1818.
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http://www.archive.org/details/alexandermackay00unknuoft/
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http://www.archive.org/details/a592254601marsuoft
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http://www.archive.org/details/hindrancestothew00unknuoft
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http://books.google.com/books?vid=ISBN0665456816&id=sipohllLjKQC&dq=protestant+missions&a_sbrr=1 View book via Google
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http://books.google.com/books?vid=ISBN0665456816&id=sipohllLjKQC&dq=protestant+missions&a_sbrr=1 View book via Google
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http://www.archive.org/details/twentyfiveyears00wattuoft
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We propose a new technique for efficiently delivering popular content from information repositories with bounded file caches. Our strategy relies on the use of fast erasure codes (a.k.a. forward error correcting codes) to generate encodings of popular files, of which only a small sliding window is cached at any time instant, even to satisfy an unbounded number of asynchronous requests for the file. Our approach capitalizes on concurrency to maximize sharing of state across different request threads while minimizing cache memory utilization. Additional reduction in resource requirements arises from providing for a lightweight version of the network stack. In this paper, we describe the design and implementation of our Cyclone server as a Linux kernel subsystem.
Resumo:
The problem of discovering frequent arrangements of temporal intervals is studied. It is assumed that the database consists of sequences of events, where an event occurs during a time-interval. The goal is to mine temporal arrangements of event intervals that appear frequently in the database. The motivation of this work is the observation that in practice most events are not instantaneous but occur over a period of time and different events may occur concurrently. Thus, there are many practical applications that require mining such temporal correlations between intervals including the linguistic analysis of annotated data from American Sign Language as well as network and biological data. Two efficient methods to find frequent arrangements of temporal intervals are described; the first one is tree-based and uses depth first search to mine the set of frequent arrangements, whereas the second one is prefix-based. The above methods apply efficient pruning techniques that include a set of constraints consisting of regular expressions and gap constraints that add user-controlled focus into the mining process. Moreover, based on the extracted patterns a standard method for mining association rules is employed that applies different interestingness measures to evaluate the significance of the discovered patterns and rules. The performance of the proposed algorithms is evaluated and compared with other approaches on real (American Sign Language annotations and network data) and large synthetic datasets.