### Table 3: Parameter estimates for the 12 herds, are parameters for the mean, = ( 2; 2; 2; ) are parameters for the variance components and are the pa- rameters for the dropout process.

1996

"... In PAGE 26: ... Thus one herd has 4 parameters to describe the mean, 4 to describe the variance components and 2 to describe the Markovian dropout process. The result after estimation of the parameters is presented in Table3 and the curves for three selected herds are shown in Figure 11. The parameter estimates for the herds roughly divide the herds into three groups.... ..."

### Table 7 Axioms for IMAC for Markovian observational congruence

"... In PAGE 29: ...able 2), (B40) (cf. Table 5), (R1) through (R3) (cf. Table 2 where guarded means strongly guarded), (RL1) through (RL3) (cf. Table 5), and the axioms listed in Table7 . This axiom system is sound and complete for strongly regular... In PAGE 30: ... Axioms ( 1)-( 3) are the usual axioms for classical weak bisimulation, and ( 4) is a direct adaption of ( 2). Note that no delayed variant of ( 3) is included in Table7 (such as ( ) : (P + :Q)+( ) :Q=( ) : (P + :Q)). This is a consequence of the fact that Markovian observational congruence treats Markovian transitions in the same way as non-internal transitions are treated in branching bisimulation (congruence).... In PAGE 34: ...B4) (cf. Table 2), (R1) through (R3) (cf. Table 2), (RL1) and (RL3) (cf. Table 5), (I1), (RL4) (cf. Table7 ) and the axioms (RL5) and (P1000) listed in Table 9. This axiom system is sound and complete for regular terms in IMC and lumping bisimulation.... In PAGE 35: ...means strongly guarded), and of ( 1) through ( 3) (cf. Table7 ), and of ( 40), ( ) : :P =( ) :P. A0 is sound and complete for strongly regular terms in IMC and lumping observational congruence.... ..."

### Table 1: Parameter values for Markovian experiments

2006

### Table 6. The Contribution of the hor- izontal and depth Dimensions (v gt; 0 Marks Parent Annotation, h gt; 0 Marks 1- Order Markov Process): FAll (WOP) per Syntactic Category on Section 0 10 The addition of an orthogonal depth dimension to the horizontal-vertical space goes beyond mere \state-splits quot; (cf. [11]) as it does not only encode re ned syntactic categories but also signals linguistically motivated co-occurrences between them.

"... In PAGE 7: ... As further illustrated in table 6 the internal structure of di erent syntactic constituents may bene t to a di erent extent from information pro- vided by di erent dimensions. Table6 shows the breakdown of the FAll(WOP) accuracy results for the main syntactic categories in our treebank. In the lack of parental context (v = 0) the Markovian head-outward process (h = 1) encodes information relevant for disambiguating the at variable phrase-structures.... ..."

### Table 3 Size of the Markovian semantic models of the six mutual exclusion algorithms

2003

"... In PAGE 41: ... The performance measures we are interested in are the mean numbers of accesses per time unit to the critical section and to the shared variables. They are computed on the Markovian semantic model of each al- gorithm; the size of such models in the case of two programs is shown in Table3 . The former performance index represents the throughput of the al- gorithm and has been specified by assigning bonus reward 1 to every action with type exec csi.... ..."

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### Table 4: System 2, 400 ms round trip delay, Markovian simulator

1999

Cited by 56