Most drift seeds are produced by tropical trees, and they can be found on distant beaches after drifting thousands of miles through ocean currents.
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These predictors, called ε-machines, are a subset of a well known statistical model class called the Hidden Markov Model (HMM). Despite being a subset, ε-machines have several important advantages over traditional HMMs. This dissertation illustrates these advantages by applying ε-machines to several problems in computer security: anomaly-based intrusion detection in High Performance Computing (HPC) environments, automated protocol reverse engineering, and structural drift.
A schooling fish of temperate waters, chub mackerel or thimbleeye migrates in much greater numbers to New Jersey than into New York waters .
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