### Tables, Schweizerbart, Stuttgart, 188 p. Wahlstrom, E.E., 1979, Optical Crystallography (5th ed.), John Wiley amp; Sons, New York, 488 p. Zimmermann, H.D., 1997, Experiments in Crystal Optics, in: Brady, J.B., Mogk, D.W. amp; Perkins, D. (eds.), Teaching Mineralogy, Mineralogical Society of America, Washington, D.C., p. 297-308.

### Table 4.1 A set of independent tasks The schedule is optimal, which is not true in general when the maximum lateness is under consideration. 19/2/1994 17:41|PAGE PROOFS for John Wiley amp; Sons Ltd (using jwcbmc01, Vers 01.02 OCT 1993)|bonas

### Tables and graphs of these data are available at http://physics.nist.gov/PhysRefData/. 3. B. Rossi, High Energy Particles, Prentice-Hall, Inc., Englewood Cli s, NJ, 1952. 4. U. Fano, Ann. Rev. Nucl. Sci. 13, 1 (1963). 5. J.D. Jackson, Classical Electrodynamics, 3rd edition, (John Wiley amp; Sons, New York, 1998).

### Table 3: Optimal release times (in minutes) and tardiness probabilities mental editor for their helpful comments and suggestions. This work was supported, in part, by grant Grant DMI-9713878 from the National Science Foundation. References Ahuja, R.K., T.L. Magnanti and J.B. Orlin, Network Flows, Prentice-Hall, 1993. Bazaraa, M.S., H.D. Sherali and C.M. Shetty, Nonlinear Programming: Theory and Algorithms, John Wiley amp; Sons, 1993. Danskin, J.M., The Theory of Max-Min and Its Applications to Weapons Allocation Problems, Springer, New York, 1967. 29

"... In PAGE 29: ...8) is veri ed here. Table3 shows the optimal release times together with the respective due dates and tardiness probabilities computed by (7.... ..."

### Table 1.7 The e ect of randomization on gather and scatter performance. Times in msec on an 8K CM{200. size. Figure 1.8 shows the execution times for two methods of accumulating the product vector: using the combining features of the router, and accumulation after the routing operation. Randomization of the addresses improved the router combining time by about a factor of two, but performing the routing without combining is even more e ective. Table 1.7 gives the gather scatter times with and without randomization for a solid mechanics application [MNT93b] on the CM{200. The performance enhancement is a factor of 1.5 { 2.2, which in our experience is typical. It is rarely the case that randomization has caused a performance degradation. 19/9/1994 17:53|PAGE PROOFS for John Wiley amp; Sons Ltd (using jwcbmc01, Vers 01.01 MAY 1992)|P4

### Table 3, which gives a mean value of 165.5 bytes.

"... In PAGE 14: ...opyright 1997 by John Wiley amp; Sons, Ltd. lt;URL: http://www3.interscience.wiley.com/ gt; 14 Table3 . Histogram for interactive traffic packet length The fractal traffic generator used is a Fractional Gaussian Noise generator implemented using a Random Midpoint Displacement algorithm.... ..."

### Table 1: Best cutsizes and runtimes for our testbed of graphs. EO and SA results are from our runs (SA parameters as determined by Johnson et al. (John- son 1989), using a 200MHz Pentium. GA results are from Merz and Freisleben (Merz 1998), using a 300MHz Pentium. Comparison data for three of the large graphs are due to results from heuristics by Hen- drickson (Hendrickson 1996), using a 50MHz Sparc20.

in GECCO Category: Evolutionary Strategies - Extremal Optimization: Methods derived from Co-Evolution

"... In PAGE 4: ... To evaluate EO, we tested the algorithm on a testbed of well-studied large graphs1 discussed in (Hendrick- son 1996, Merz 1998). Table1 summarizes EO apos;s re- sults on these, using 30 runs of at most 200N up- date steps (though in several cases far fewer). On the rst four large graphs, SA apos;s performance is extremely poor; we therefore substitute results given in (Hen- drickson 1996) using a variety of specialized heuristics.... ..."

### Table 3: The OSEL Taxonomy Preliminary Taxonomy of the types of LO (Wiley)

2006

"... In PAGE 7: ... In the OSEL Tax- onomy columns 4 and 5 of Table 2 have been deleted, as the distinction between LO having Computer- generated instruction and / or practice and Domain-specific presentation strategies is useless for the classification the group is working on. Table3 represents the OSEL Taxonomy, which focuses on the in- trinsic characteristics of the LO and the interaction with the user, and not on the remarks of the author on the contents, which can eventually be found by a semantic engine in the ADL/SCORM data once the LO ... ..."

Cited by 1

### Table 3: Results for the John vector

in Discovery of Tacit Knowledge and Topical Ebbs and Flows within the Utterances of Online Community