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Apr 17, 2019 · Optical character recognition (OCR) software converts pictures, or even handwriting, into text.​ OCR software analyze a document and compare it with fonts stored in their database and/or by noting features typical to characters.​ Some OCR software also put it through a spell checker ... The 13 Best New OneNote ... · 4 Free Online OCR Tools Put ...

Several recent measurement studies have concluded that classical Poisson-like traf c models do not account for time dependencies observed at multiple time scales in a wide range of networking applications, for example, Ethernet LANs [13, 20, 33], variable bit rate (VBR) traf c [3, 15], Web traf c [6], and WAN traf c [31]. As the resulting temporal correlations are expected to have a signi cant impact on buffer engineering practices, this ``failure of Poisson modeling'' has generated an increased interest in a number of alternative traf c models that capture observed (long-range) dependencies [14, 24]. Proposed models include fractional Brownian motion [25] and its discrete-time analog, fractional Gaussian noise [1]. Already both have exposed clearly the limitations of traditional traf c models in predicting storage requirements and devising congestion controls. A discussion of these issues in the case of fractional Brownian motion is summarized in 4. In this chapter we focus instead on the class of M =G=I input processes as potential traf c models. An M =G=I input process is understood as the busy server process of a discrete-time in nite server system fed by a discrete-time Poisson process of rate l (customers=slot) and with generic service time s distributed according to G. As argued in Parulekar [27] and Parulekar and Makowski [29], these M =G=I input processes constitute a viable alternative to existing traf c models; reasons range from exibility to tractability.



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Filesystem backups vary by operating system On Windows, there is an issue with backing up open files If an application has a file open, the file is locked A locked file cannot be accessed by any other applications Obviously, in order to back up a file, a backup utility must access the file If the utility cannot access (or lock) a particular file, it will timeout in its attempt to back up the file, and move on When this occurs, the locked file will not get backed up at all There are at least two utilities for assisting in the backing up of open Windows files: St Bernard s Open File Manager and Columbia Data Systems Open Transaction Monitor Some Windows backup manufacturers integrate one of these products right into their software, while others deliver their own.





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Self-Similar Network Traf c and Performance Evaluation, Edited by Kihong Park and Walter Willinger ISBN 0-471-31974-0 Copyright # 2000 by John Wiley & Sons, Inc.

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These utilities operate in kernel mode, filtering I/O for calls to open or locked files They keep a copy of the open file in cache memory and present that copy to the backup software In this way, this software guarantees that a consistent copy of the file gets backed up The open file management software may also be able to cache the entire filesystem in memory (or on another disk) and present a consistent and unchanging copy of the filesystem to the backup utility On Unix, open files are not as much of an issue A file that is written to disk can be backed up by reading it off the disk If a file is open and being written to, then the disk copy of the file may not reflect its most recent contents, but your backup will get the most recent copy that is on the disk.

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First, the relevance of the M =G=I input model to network traf c modeling is perhaps best explained through its connection to an attractive model for aggregate packet streams proposed by Likhanov et al [21] They show that the combined traf c generated by several independent, identically distributed (iid) on=off sources with Pareto distributed activity periods behaves in the limit, as the number of sources increases, like the M =G=I input stream with a Pareto distributed s This provides a rationale for the view that M =G=I input processes could provide a natural alternative to existing traf c models, at least for certain multiplexed applications Second, the class of M =G=I input processes is stable under multiplexing; that is, the superposition of several M =G=I processes can be represented by an M =G=I input process.

Third, the M=G=I model displays great exibility in capturing positive dependencies over a wide range of time scales; this is achieved very simply through the tail behavior of s (Proposition 941) The degree of positive correlation can further be characterized by the sum of the autocovariances, or index of dispersion of counts (IDCs), with the process being short-range dependent (SRD) (ie, IDC nite) if and only if E s2 is nite (Proposition 951) Insights into how temporal correlations of M=G=I input processes will affect queueing performance can be gained by analyzing the behavior of a multiplexer fed by an M =G=I input process For simplicity, we model the multiplexer as a discretetime single server system consisting of an in nite size buffer and a server with a constant release rate c (cells=slot).

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