read pdf in asp.net c#

how to read pdf file in asp.net using c#

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Read or load a PDF file and extract its text content in C# and VB. NET application with GemBox.Document library.

assuming that < 1 If < 1, the transient probabilities pij (t) converge to the equilibrium probabilities pj = (1 ) j as t and, similarly, E[L(i, t)] converges to /(1 ) as t A natural question is how fast the convergence occurs A heuristic answer to this question has been given by Odoni and Roth (1983) 2 in the context of the M/G/1 queue Letting cS denote the squared coef cient of variation of the service time, the M/G/1 queue will forget its initial state after a time comparable to 2 (1 + cS )E(S) trelax = 28(1 )2 provided that the system is empty at epoch 0

read pdf in asp.net c#

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how to read pdf file in asp.net using c#

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In general the linear differential equations (451) have to be solved numerically Let us assume in the remainder of this section that the state space I of the Markov chain is nite There are several possibilities to numerically solve the homogeneous system (451) of linear differential equations with constant coef cients In most applications the matrix of coef cients has distinct eigenvalues and is thus diagonalizable In those situations one might compute the eigenvalues 1 , , n of the matrix and the corresponding eigenvectors The transient probabilities pij (t) are then a linear combination of pure exponential functions e 1 t , , e n t (zero is always among the eigenvalues and the corresponding eigenvector gives the equilibrium distribution of the Markov process up to a multiplicative constant) In general, however, one uses a so-called Runge Kutta method to solve the linear differential equations numerically Standard codes for this method are widely available From a numerical point of view, the Runge Kutta method is in general superior to the eigenvalue approach The Runge Kutta method has the additional advantage that it can also be applied to continuous-time Markov processes with timedependent transition rates Another possible way to compute the pij (t) is to use the discrete FFT method when an explicit expression for the generating function P (t, z) = j I pij (t)zj , |z| 1 is available 452 The Uniformization Method This method falls back on an earlier construction of a continuous-time Markov chain in Section 41 In this construction the process leaves state i after an exponentially distributed time with mean 1/ i and then jumps to another state j (j = i) with probability pij Letting Xn denote the state of the process just after the nth state transition, the discrete-time stochastic process {Xn } is an embedded Markov chain with one-step transition probabilities pij The jump probabilities pij and the in nitesimal transition rates qij are related to each other by qij = i pij , i, j I with j = i (452).

read pdf file in asp.net c#

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read pdf in asp.net c#

how to read pdf file in asp.net using c#