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NeOCR is a free software based on Tesseract ( Open Source OCR Engine) for the Windows operating system. It provides an easy and user-friendly user interface to recognize texts contained in images as well as PDF documents and convert to editable text formats (.txt, .doc, .docx).

In the rst case, we assume that both traf c processes are in the same state with the same initial condition characterized by the amount of traf c left in the system when the processes enter the state In the second case, we consider two-state Markov and LRD uids To examine whether it is appropriate to predict loss performance computed according to Markov models in steady state for LRD traf c, in Section 134, we show how to compute steady-state limits of transient loss measures for general two-state uids, and compare transient loss against loss in steady state In Section 135, we discuss the impact of long-range dependence in network traf c, based on the analytical and numerical results obtained We conclude this chapter in Section 13.



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Feb 5, 2019 · Let's have a look at the Top Best Free OCR Software of 2019 that will help you to convert the image printed text into the editable document.

6, with a summary of the ndings of our study, and a brief discussion on the challenge posed by transient performance guarantee in the presence of longrange dependence and some extension of this work Section 137 contains two appendixes 132 TRAFFIC MODELS AND TRANSIENT LOSS MEASURES.

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We adopt general uid-type stochastic processes with multiple states as a framework for traf c modeling. The state of such a process is associated with the bit rate of the underlying traf c source. When the process is in a given state, the source generates traf c at a constant bit rate. The bit rates are different for different states. Such uidtype traf c models have been used in many previous studies for traf c engineering. A well-known example is the Markov-modulated uid model [5]. However, the traf c model in our study is essentially different from traditional uid traf c models: our traf c model is not necessarily Markovian, which allows us to capture the

property of long-range dependence in traf c A special case of our traf c model is the general two-state uid, which can capture the most important traf c properties such as long-range dependence and burstiness An important part of this work is based on the two-state uid model Various on=off uid models are special cases of the general two-state uid and have widely been used for traf c modeling For example, on=off sources with heavy-tailed on=off periods are proposed to explain long-range dependence or self-similarity in traf c [18] For an on=off uid, no traf c is generated in the off state In this book, on=off traf c models are also considered in s 5, 7, 11, and 17 Let us denote a uid-type traf c process by R t The physical meaning of R t is the time-dependent bit rate of the underlying traf c source.

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