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Table 1 Coupled Soliton/Soliton Collisions Note: \Re ection quot; means that the soliton velocities change sign. \Elastic quot; implies that the solitons lose little energy during the collision. \Exchange quot; means that the Mode 2 component is transferred from its original partner to the other soliton which was initially in Mode 1 only. \Crossing quot; means that the solitons freely interpenetrate and then continue with unchanged direction.

in Coupled-Mode Envelope Solitary Waves in a Pair of Cubic Schrödinger Equations with Cross Modulation: Analytical Solution and Collisions with Application to Rossby Waves
by Benkui Tan, John P. Boyd 1999
"... In PAGE 15: ... Instead, it becomes highly oscillatory in both modes; the A2 part (right middle plot) continues to radiate away energy indeflnitely. At high velocity, we have described the interaction in Table1 as a \Crossing quot; rather than an \Ex- change quot; because the interacting solitary waves merge into a single structure during the collision whereas in Fig. 5, the contours of the interacting solitons always remain distinct and spatially separated so that the label \Crossing quot; seems inappropriate.... ..."
Cited by 2

Table 1: Branch predictor configurations evaluated. 4.1 Program Level Potential for Branch Predictor Adaptation At the program level, IPC, ED2, total processor energy, and branch predictor energy were plotted for each benchmark, for each branch predictor simulated. Results show that when examining the raw data, there is little potential for adapting branch predictor configuration at the program level to make energy efficiency gains. To verify this, percent difference of each branch predictor from the overall best branch predictor was calculated and plotted.

in Potential for Branch Predictor Adaptation at the Program and Phase Level for Performance and Energy-Efficiency
by Michele Co, Dee A. B. Weikle, Kevin Skadron 2005

Table 4: Note the improvement in prediction accuracy on the supposedly more difficult and longer E. coli RNase P data-set. This shows that MFE methods are less sensitive to folding errors on longer data-sets but are also less likely to resolve the entire structure. There is little difference in algorithm accuracy for each of the methods explored here. Each employs the same energy parameters so differences are due to slightly different implementations.

in unknown title
by unknown authors 2004

Table 8.2 shows the mean energy consumed per sensor per message for various message encod- ing formats. As expected, we see that using the ASCII based XML format, both the transmission and reception energy consumed is almost 9 times higher than that of the custom encoding approach. On the other hand, the use of a compact binary XML encoding format (with predetermined, sep- arated XML schema) consumes the same amount of energy as that of a custom encoding format. As explained in Section 8.5, completely customized protocols are most energy-efficient but offer very little flexibility and interoperability. Whereas the textual XML represents the other end of the spectrum. Using XML has a number of attractive benefits, but the verbosity incurs large energy costs during communication (almost 9 times higher than the custom based formats). However, the use of binary XML is a compromise between textual XML and custom formats. These results helped us to validate our simulation framework.

in Towards A Holistic Approach for Protocol Development in Sensor Networks
by Sameer Tilak 2005

Table 2 shows that if a worse estimate is adopted to start with then the method will still provide accurate results in those regions that contribute most to the energy integral but that errors in the repulsive region for example are hardly corrected so that the Fourier grid method says little, and the RKR method says nothing, concerning the potential in the repulsive region. The potential generated to give the experimental energies is not unique, as can be seen from table 2. If no better estimates are available then, for example, a combination of a Morse potential and a long range potential of the form (6) can be used to start the calculation and the results may be good enough for some scattering calculations. It is possible to directly generate a parametrized potential using this method. Thus if V is a function of Np parameters V.R/DV. 1::: pjR/ (27)

in unknown title
by unknown authors 1999
"... In PAGE 5: ...1189 Table2 . The starting potentials V0, V1 and the calculated potentials Vcalc for H2.... ..."

Table 6: Simulation results for 64K, 2-way set associative L1 D-cache. Miss bound is 1%, and Sense interval is 1 million

in CS/ECE752 Fall 2001 Course Project Study of L1 D-cache with Adaptive Associativity for Leakage Power Reduction
by unknown authors
"... In PAGE 13: ...enchmarks mgrid and wave5, we get very little leakage energy saving. The last column reveals the possible reason. These three benchmarks almost make full use of the 4 cache ways, therefore, little leakage energy saving is achieved. Table6 shows the results for 64k, 2-way set associative L1 D-cache. Similarly, most of the benchmarks can achieve large leakage energy reduction with only small percentage of dynamic energy increment.... ..."

Table 6: energy consumed and % packets dropped by the history based approach

in Wireless Network Interface Energy Consumption Implications of Popular Streaming Formats
by Surendar Chandra 2002
"... In PAGE 24: ...Table 6: energy consumed and % packets dropped by the history based approach little worse under lossy network conditions. The results for the different formats under varying network bandwidth and loss parameters are tabulated in Table6 . We note that significant energy consumption gains with minimal data loss can be expected for formats which tend to packets at a constant rate.... ..."
Cited by 42

Table 6: energy consumed and % packets dropped by the history based approach

in Wireless Network Interface Energy Consumption Implications of Popular Streaming Formats
by Surendar Chandra 2002
"... In PAGE 24: ...Table 6: energy consumed and % packets dropped by the history based approach little worse under lossy network conditions. The results for the different formats under varying network bandwidth and loss parameters are tabulated in Table6 . We note that significant energy consumption gains with minimal data loss can be expected for formats which tend to packets at a constant rate.... ..."
Cited by 42

Table 1. 3H and 4He binding energies obtained with different NN force models compared to the experi- mental values.

in Few-Baryon Systems
by Walter Glöckle, Henryk Witala, Jacek Golak, Andreas Nogga, Horst Rollnik, Dietrich Wolf (editors, Walter Gl Ockle, Walter Gl Ockle, Hiroyuki Kamada, Hiroyuki Kamada
"... In PAGE 4: ... The amount of extension of the nucleons shown as little balls is just an artistic view. The binding energies (in units of MeV) are presented in Table1 for various high precision NN forces and compared to the experimental values. We see, theory and experimental values disagree.... ..."

Table 1. 3H and 4He binding energies obtained with different NN force models compared to the experi- mental values.

in Few-Baryon Systems
by Walter Glöckle, Henryk Witała, Jacek Golak, Hiroyuki Kamada, Andreas Nogga, Horst Rollnik, Dietrich Wolf (editors, Walter Glöckle, Henryk Witała, Jacek Golak, Hiroyuki Kamada, Andreas Nogga
"... In PAGE 4: ... The amount of extension of the nucleons shown as little balls is just an artistic view. The binding energies (in units of MeV) are presented in Table1 for various high precision NN forces and compared to the experimental values. We see, theory and experimental values disagree.... ..."
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