### Table 2. Results of using crude initial schedules generated by simple heuristics.

### Table A.IV. Performance of Other Systems

1996

Cited by 54

### TABLE ELAPSED TIME

1992

Cited by 1

### Table 2: Elapsed time

2001

"... In PAGE 18: ...ts torso. With our body center position estimation, the number of iterations decreases significantly. In most cases, our estimation algorithm finds the body position that makes the end-effectors reachable to their goal positions without any help of the numerical solver. Table2 gives an overall performance of our on-line motion retargetting algorithm excluding ren-... ..."

### TABLE 2: Times (in milliseconds) to search approximate patterns in suffix tree/array indexes. They are separated in CPU time ( u ) and I/O time ( s ).

2000

Cited by 39

### Table 4. Query time for medium patterns and for k = 2, 4 and 6. The on-line algo- rithm shows time in milliseconds in the format \user/system quot;, in italics. The indexed algorithms show the fraction they take of the time of the on-line algorithm. The format is \a=b quot;, where a considers only user time and b considers both. The fastest indexed times are in boldface. Acknowledgements We thank the nice comments of two referees, which helped to improve this work. We also thank Erkki Sutinen for his code to build the su x tree, and Gene Myers and Archie Cobbs for sending us their implemented indices.

1999

Cited by 12

### Table 3. Modelling the Elapsing of Time

1999

"... In PAGE 7: ... It is worth of note that two subsequent transitions, such as d =) M i d0 and d0 =) M j d00 may occur at di erent times (time elapses), while regarding the transition relation ?! M i we always have i = j. The inference rules de ning the elapsing of time are given in Table3 . There, up is a function which given a process d and a natural number n updates to n every relative local clock appearing within d (e.... ..."

Cited by 1

### Table 2: Elapsed time for analysis

"... In PAGE 28: ... They represent the two extreme cases: in counter, method invocations are much more frequent than creations of concurrent objects, while in tree14, creations of concurrent objects happen as frequently as method invocations do. Table2 shows the elapsed time by our analysis for the same set of benchmark programs. We have implemented our analysis with the subtyping relation precedesequalNonStr, written in Standard ML of New Jersey 0.... ..."

### Table 8 Wesdyn elapsed times

1993

"... In PAGE 9: ... Hence, we expect that if dif- ferences in communication performance were signi cant, this application (rather than an embarrassingly parallel, compute bound problem) would expose those di erences. The results of this comparison are given in Table8 . Notice that the TCGMSG program runs at about the same speed as the C{Linda program for small numbers of nodes but by three nodes, it is on the order of 10% slower.... ..."

Cited by 29