### Table 3. Results for Australian institutions A B C D E F G

2007

"... In PAGE 13: ...Applying this metric would give the universities of Sydney and Melbourne the highest share of government floor funding (see Table3 , column G). As a general trend it seems clear that the larger universities (Go8 Universities) do well from a formula- based funding of the proposed type.... In PAGE 13: ... As a general trend it seems clear that the larger universities (Go8 Universities) do well from a formula- based funding of the proposed type. This is partly because of the quality dimension (displayed in column E, Table3 ) which is given a heavy weight in this model. ANU has fewer articles than New S Wales Univ, but in the end the summation of Waring value and CPP/FCSm gives ANU a higher figure.... ..."

### Table 1. early semantics (symmetric rules omitted) 3 P/T Nets with Inhibitor Arcs We recall simple Place/Transition nets without capacity constraints on places (see, e.g., [10]). Then, we extend them with the so-called inhibitor arcs (see, e.g., [13, 14, 18]). Here we provide a characterization of this model which is convenient for our aims. De nition2. Given a set S, a nite multiset over S is a function m : S ! ! such that the set dom(m) = fs 2 S j m(s) 6 = 0g is nite. The multiplicity of an element s in m is given by the natural number m(s). The set of all nite multisets over S, denoted by Mfin(S), is ranged over by m. A multiset m such that dom(m) = ; is called empty . The set of all nite sets over S is denoted by

1995

"... In PAGE 4: ... The de nitions of substitution and alpha conversion are standard, with the use of renaming to avoid name clashes. The (early) operational semantics for the -calculus is the labelled transition system generated by the rules listed in Table1 . The labels of the transitions are of four di erent kinds: the silent action , the input xy, the free and bound outputs xy and x(y).... ..."

Cited by 16

### Table 1: Characterisation of test set (1). This table lists the number of transitions, the number of states, the number of words of the actual utterances, the average number of transitions per word, the maximum number of transitions, and the maximum number of states. The rst row provides those statistics for the input word graph; the second row for the so-called normalised word graph in which all -transitions (to model the absence of sound) are removed. The number of transitions per word is an indication of the extra ambiguity for the parser introduced by the word graphs in comparison with parsing of an ordinary string.

2003

### Table 1 shows the predicates used to record properties of individuals for the analysis of our running example. We also define additional so-called instru- mentation predicates to capture properties of individuals such pointer-aliasing, sharing, cyclicity, and transitive reachability. As observed in [26], instrumenta- tion predicates provide for more precise information when applying abstraction on a concrete semantics. In particular, in Table 1 we define instrumentation pred- icate that capture reachability information (via predicates of the form rx,n(v)), sharing information (via the predicate is(v)) and information on cycles in the heap graph (via the predicate cn(v)).

2005

"... In PAGE 4: ... In the sequel, we assume that the vocabulary P is fixed, and abbreviate 2-STRUCT[P] to 2-STRUCT. Table1 . Predicates used for shape analysis of the running example, and their meaning.... In PAGE 22: ...emory deallocation, e.g., through a free directive. The actual instantiation involves a bidirectional, dual-stage analysis to con- clude future usage information for each heap allocated object, at all program locations, as it was sketched in Example 3. The first (forward) stage tracks shape related information (see Table1 ) but keeps the use(v) predicate value to be 1/2 for all individuals v, by that representing non-deterministic interpreta- tion of it. The second (backward) stage assumes false (0) value for use(v) for all v, then updates its value where a dereference expression evaluates to v.... ..."

Cited by 3

### Table 1 shows the predicates used to record properties of individuals for the analysis of our running example. We also define additional so-called instru- mentation predicates to capture properties of individuals such pointer-aliasing, sharing, cyclicity, and transitive reachability. As observed in [26], instrumenta- tion predicates provide for more precise information when applying abstraction on a concrete semantics. In particular, in Table 1 we define instrumentation pred- icate that capture reachability information (via predicates of the form rx,n(v)), sharing information (via the predicate is(v)) and information on cycles in the heap graph (via the predicate cn(v)).

2005

"... In PAGE 4: ... In the sequel, we assume that the vocabulary P is fixed, and abbreviate 2-STRUCT[P] to 2-STRUCT. Table1 . Predicates used for shape analysis of the running example, and their meaning.... In PAGE 22: ...emory deallocation, e.g., through a free directive. The actual instantiation involves a bidirectional, dual-stage analysis to con- clude future usage information for each heap allocated object, at all program locations, as it was sketched in Example 3. The first (forward) stage tracks shape related information (see Table1 ) but keeps the use(v) predicate value to be 1/2 for all individuals v, by that representing non-deterministic interpreta- tion of it. The second (backward) stage assumes false (0) value for use(v) for all v, then updates its value where a dereference expression evaluates to v.... ..."

Cited by 3

### lable there exists a state-feedback controller , u(t) = ?Kx(t), such that the poles (eigenvalues) of the closed-loop system can be located arbitrarily. State-space theory for feedback design was introduced by Kalman in the early sixties [10].Many text books are now available on this approach, see for example [9]. One state-space design theory, which is especially well suited for multivariable feedback systems, is the so-called linear-quadratic (LQ) theory. In the LQ theory the problem is to nd a state- feedback control law which minimizes an integral quadratic per- formance measure of the form

### TABLE IV COMPARISON BETWEEN THE THROUGHPUT OF THE TP-ALGORITHM AND THE, SO-CALLED, SHORTEST PATH SCHEME THAT ACHIEVES THE MAXIMUM THEORETICAL THROUGHPUT.

2003

Cited by 8

### TABLE III COMPARISON BETWEEN THE THROUGHPUT OF THE TP-ALGORITHM AND THE, SO-CALLED, SHORTEST PATH SCHEME THAT ACHIEVES THE MAXIMUM THEORETICAL THROUGHPUT.

2003

Cited by 8

### TABLE III COMPARISON BETWEEN THE THROUGHPUT OF THE TP-ALGORITHM AND THE, SO-CALLED, SHORTEST PATH SCHEME THAT ACHIEVES THE MAXIMUM THEORETICAL THROUGHPUT.

2003

Cited by 8

### Table 2: The transition system

1994

"... In PAGE 6: ... This semantics is a suitable base for reasoning about synchronization approximation, since it separates the choice operator from the synchronization operator (while in the standard semantics their interaction gives the so-called demonic nondeterminism or indeterminism). The angelic transition system T0, yelding the operational semantics O0, is obtained by imposing n = 1 in rule R2 of Table2 and by adding rule R6: h n i=1 Ai ; i !h Ai ; i. [16] de nes the nite semantics of deterministic cc languages (without choice operator) as a lower closure operator5 (lco) on BC (the set of nite elements of the constraint system C), mapping divergent computations to false.... ..."

Cited by 12