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applied for the call The location of the called subscriber determines, amongst others, whether BOR is permissible for the call When the calling party in Figure 480 sets up the call to the UK-based destination, the SCP cannot know whether BOR will be applied for this call As a result, the service cannot know how to rate this call CAMEL phase 4 has improved interaction with BOR An SCP may determine whether BOR should be applied to the outgoing call CAMEL phase 4 enables the SCP to instruct the VMSC to initiate BOR 4811 Terminating Call Handling with BOR One aspect with BOR is the terminating call handling for the called subscriber The called party may have a terminating CAMEL subscription Hence, the HLR sends the T-CSI to the GMSC in the IPLMN The HLR veri es that the GMSC supports the required CAMEL phase before sending T-CSI If the terminating call is subject to on-line charging, then the on-line charging may be applied directly in the GMSC in the IPLMN However, if BOR results in a terminating call leg within the IPLMN (as in Figure 480), then the terminating call may be toll-free for the called party However, this may differ per operator If the terminating CAMEL service involves the use of announcements, then the HPLMN operator should ensure that the GMSC in the IPLMN has the required announcements installed The availability of appropriate announcements should be part of the BOR agreement between operators 4812 Call Forwarding with BOR The terminating call in combination with BOR may lead to early call forwarding, late call forwarding or ORLCF Operators may decide to prevent call forwarding in combination with BOR, since this may lead to uncommon call cases For example, if the call in Figure 480 leads to early call forwarding, then there will be a forwarding call leg from the GMSC to, for example, the voice mail box in the HPLMN of the called party The called party may be charged for this international call forwarding leg 482 Immediate Service Termination Immediate service termination (IST) is speci ed in GSM TS 0232 [7] and GSM TS 0335 [33] IST is a network feature that enables an operator to immediately terminate ongoing services from.

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Many good textbooks on stochastic processes are available and most of them treat the topic of Markov chains My favourite books include Cox and Miller (1965), Karlin and Taylor (1975) and Ross (1996), each offering an excellent introduction to Markov chain theory A very fundamental treatment of denumerable Markov chains can be found in the book of Chung (1967) An excellent book on Markov chains with a general state space is Meyn and Tweedie (1993) The concept of the embedded Markov chain and its application in Example 313 are due to Kendall (1953) The idea of using the geometric tail behaviour of state probabilities goes back to Feller (1950) and was successfully used in the papers of Everett (1954) and Takahashi and Takami (1976)

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i want to read . pdf file using c# . net code and have to save that file ... ... ITextExtractionStrategy itextextStrat = new iTextSharp.text. pdf .parser.SimpleTextExtractionStrategy(); ... extractText = Encoding.UTF8.GetString(ASCIIEncoding.Convert(Encoding.Default, Encoding.UTF8, Encoding ...
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Chung, KL (1967) Markov Chains with Stationary Transition Probabilities, 2nd edn Springer-Verlag, Berlin Cox, DR and Miller, HD (1965) The Theory of Stochastic Processes Chapman and Hall, London Everett, J (1954) State probabilities in congestion problems characterized by constant holding times Operat Res, 1, 279 285 Feller, W (1950) An Introduction to Probability Models and its Applications, Vol I, John Wiley & Sons, Inc, New York Fox, B and Landi, DM (1968) An algorithm for identifying the ergodic subchains and transient states of a stochastic matrix Commun ACM , 11, 619 621 Karlin, S and Taylor, HM (1975) A First Course in Stochastic Processes, 2nd edn Academic Press, New York Kendall, DG (1953) Stochastic processes occurring in the theory of queues and their analysis by the method of the embedded Markov chain Ann Math Statist, 24, 338 354 Markov, AA (1906) Extension of the law of large numbers to dependent events (in Russian) Bull Soc Phys Math Kazan, 15, 255 261 Meyn, SP and Tweedie, R (1993) Markov Chains and Stochastic Stability Springer-Verlag, Berlin Ross, SM (1996) Stochastic Processes, 2nd edn, John Wiley & Sons, Inc, New York Stewart, WJ (1994) Introduction to the Numerical Solution of Markov Chains Princeton University Press, Princeton NJ Takahashi, Y and Takami, Y (1976) A numerical method for the steady-state probabilities of a GI /G/c queueing system in a general class J Operat Res Soc Japan, 19, 147 157

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8 Nov 2017 ... In this section we will discuss how to read text from PDF files . ... reference ( iTextSharp.dll) to project. http://sourceforge. net /projects/itextsharp/.

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Read a PDF file using C# .Net | The ASP . NET Forums
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In the continuous-time analogue of discrete-time Markov chains the times between successive state transitions are not deterministic, but exponentially distributed However, the state transitions themselves are again governed by a (discrete-time) Markov chain Equivalently, a continuous-time Markov chain can be represented by so-called in nitesimal transition rates This is in analogy with the t-representation of the Poisson process The representation by in nitesimal transition rates leads naturally to the ow rate equation approach This approach is easy to visualize and is widely used in practice The continuous-time Markov chain model is introduced in Section 41 In Section 42 we discuss the ow rate equation approach The discussion in Section 42 concentrates on giving insights into this powerful approach but no proofs are given The proofs are given in Section 43 Results for discrete-time Markov chains are the basis for the proofs of the ergodic theorems for continuous-time Markov chains In Section 44 we discuss specialized methods to solve the equilibrium equations for continuous-time Markov chains on a semi-in nite strip in two-dimensional space Many applications of continuous-time Markov chains have this structure Section 45 deals with transient analysis for continuous-time Markov chains The basic tools for the computation of the transient state probabilities and rst passage time probabilities are Kolmogoroff s method of linear differential equations and the probabilistic method of uniformization Both methods will be discussed In Section 46 we give algorithms for the computation of the transient probability distribution of the cumulative reward in a continuous-time Markov chain model with a reward structure A special case of this model is the computation of the transient distribution of the sojourn time of the process in a given set of states

A First Course in Stochastic Models HC Tijms c 2003 John Wiley & Sons, Ltd ISBNs: 0-471-49880-7 (HB); 0-471-49881-5 (PB)

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Read a PDF file using C# .Net | The ASP . NET Forums
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