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TABLE V FIXED POWER SCHEDULING (GRID DISTRIBUTION).

in Scheduling Optimization in Wireless MESH Networks with Power Control and Rate Adaptation
by unknown authors

TABLE VI POWER CONTROL SCHEDULING (GRID DISTRIBUTION).

in Scheduling Optimization in Wireless MESH Networks with Power Control and Rate Adaptation
by unknown authors

Table 3: Weighted mean relative difference of estimated with actual flow length distributions, calculated blockwise. CAMPUS dataset

in ABSTRACT Estimating Flow Distributions from Sampled Flow Statistics
by Nick Duffield
"... In PAGE 9: ... This enables us to factor out the smoothing from the comparison, so comparing the effects of the different choice of block bound- aries. The WMRD values are shown in Table3 . This shows x62 f(2) to be uniformly better than x62 f(1) in predicting the block weights.... In PAGE 10: ... Nonetheless, we expect that discrepancies in the distribution of single flow lengths of roughly 20% may be acceptable for some applications. If only coarser distributional information is required, Table3 shows the block aggregates to be considerably more accurate. 7.... ..."

Table 2 shows the approximate power estimation of this application calculated using the power

in TMS320DM6467 Power Consumption Summary
by unknown authors 2008

Table 6: Three Technologies for Application

in Implementation of a Technology Impact Forecast Technique on a Civil Tiltrotor
by Dimitri Mavris Andrew, Andrew P. Baker, Daniel P. Schrage 1999
"... In PAGE 8: ... This formulation ensures that technology modeling can handle both the primary benefit and secondary degradation of appropriate metrics. Table6 provides the metric values used for the three technologies... In PAGE 11: ... Thus the application of three technologies provides the desired improvement in DOC+I with no other technologies needed. However, suppose the projected improvement in O amp;S cost (see Table6 ) is over-optimistic for the smart green engine. This environment allows the decision maker to determine 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0.... ..."
Cited by 5

Table 1: SmartBadge components

in Dynamic Power Management for Portable Systems
by Tajana Simunic, Luca Benini, Peter Glynn, Giovanni De Micheli 2000
"... In PAGE 4: ... Similar to the hard disk, the transition from standby into the active state can be best described using the uniform probability distribution. Com- ponents in the SmartBadge, the power states and the transi- tion times of each component from standbyinto activestate are shown in the Table1 . Note that the SmartBadge has twotypes of data memory { slower SRAM (1MB, 80ns) from Toshiba and faster DRAM (4MB, 20ns) from Micron that is used only during MPEG decode.... ..."
Cited by 100

Table 1 Computing time for grid generation and Euler flow calculation algorithms for each test case measured in terms of cpu-time and percentage of an 8 hour working day (m=minutes; s=seconds); cpu-time of grid generation measured on workstation (MIPS R10000); cpu-time of flow calculation (including pre-processing) measured on single processor of NEC SX4/16 supercomputer

in FASTFLO-automatic CFD system for threedimensional flow simulations
by J.W. van der Burg, B. Oskam, Nationaal Lucht- En Ruimtevaartlaboratorium
"... In PAGE 8: ...NLR-TP-97556 L 4 Applications Four applications are introduced to review the characteristics of the FASTFLO CFD system, see Table1 and 2. Examples are shown for case 2 in Figure 2, for case 3 in Figure 3 and for case 4 in Figure 4.... In PAGE 8: ... The flow solution is obtained by taking a sufficient number of multigrid cycles. The computing time of the FASTFLO CFD system for these four cases is limited as can be ob- served in Table1 . The grid dimensions for each case can be found in Table 2.... ..."

Table 2. Iterations needed for calculating a balancing flow for BG A2 DC Grid and Torus.

in Toward Optimal Diffusion Matrices
by Robert Elsässer, Burkhard Monien, Stefan Schamberger, Günther Rote 2002
"... In PAGE 7: ... The results for Grid and Torus given in Figures 5 and 6 differ from the others in the way that large savings of iterations are possible, what is due to the large value of CP D3D4D8 . As shown in Table2 and 3, savings up to 28% can be archived. Note, that by fixing one dimension and increasing the other dimension to infinity, the optimal value of CP will grow quadratically with the cardinality of the graph in the second dimension leading to improvements up to a factor of BE.... ..."
Cited by 1

Table 2. Iterations needed for calculating a balancing flow for BG A2 DC Grid and Torus.

in Toward Optimal Diffusion Matrices
by Robert Elsässer, Burkhard Monien, Stefan Schamberger, Günter Rote 2002
"... In PAGE 7: ... The results for Grid and Torus given in Figures 5 and 6 differ from the others in the way that large savings of iterations are possible, what is due to the large value of CPD3D4D8. As shown in Table2 and 3, savings up to 28% can be archived. Note, that by fixing one dimension and increasing the other dimension to infinity, the optimal value of CP will grow quadratically with the cardinality of the graph in the second dimension leading to improvements up to a factor of BE.... ..."

Table 2. Iterations needed for calculating a balancing flow for BG A2 DC Grid and Torus.

in Toward Optimal Diffusion Matrices
by Robert Elsässer, Burkhard Monien, Stefan Schamberger, Günther Rote 2002
"... In PAGE 7: ... The results for Grid and Torus given in Figures 5 and 6 differ from the others in the way that large savings of iterations are possible, what is due to the large value of CPD3D4D8. As shown in Table2 and 3, savings up to 28% can be archived. Note, that by fixing one dimension and increasing the other dimension to infinity, the optimal value of CP will grow quadratically with the cardinality of the graph in the second dimension leading to improvements up to a factor of BE.... ..."
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