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Table 2. Spatial Correlation of Model AOD with TOMS AAI and AODa

in unknown title
by unknown authors
"... In PAGE 11: ...reted as the fraction of the spatial variance (i.e., structure) explained by the model. Table2 shows the spatial variance in the TOMS AAI observations explained by each model (r2). The three hypotheses with spatially heterogeneous erodibility factors match the spatial structure of TOMS AAI better than the Uniform erodibility, which performs worst in Africa and Australia (Figures 5d and 5f).... In PAGE 11: ... The best performance in Africa, East Asia, and Australia is achieved by the Topographic, Geomorphic, and Hydrologic erodibil- ity, which explain 47%, 83%, and 49% of the observed spatial structure, respectively (Figures 5g, 5k, and 5o). [48] Figure 5 and Table2 show that different erodibility hypotheses may prevail in different regions. We estimated the range of spatial variability explained by heterogeneous erodibility by subtracting r2 from the Uniform case from the r2 of the heterogeneous hypotheses in each region.... ..."
Cited by 2

Table 8: The e#0Bects of sampling rate on error #28tom-

in Using Branch Handling Hardware to Support Profile-Driven Optimization
by Thomas M. Conte, Burzin A. Patel, J. Stan Cox 1994
Cited by 32

Table 2: Simulation times for scanning the human-liver phan- tom.

in Fast Simulation of Ultrasound Images
by Jørgen Arendt Jensen, Jrgen Arendt Jensen, Svetoslav Ivanov Nikolov, Svetoslav Ivanov Nikolov 2000
"... In PAGE 4: ...2. The various simulation times are shown in Table2 . These data also include the beam focus- ing for the synthetic aperture simulation, which took 9 sec- onds in all cases.... ..."
Cited by 1

Table 2. Spatial Correlation of Model AOD with TOMS AAI and AODa

in Spatial Heterogeneity in Aeolian Erodibility: Uniform, Topographic, Geomorphologic, and Hydrologic Hypotheses
by Hydrologic Hypotheses, Charles S. Zender, David Newman, O. Torres 2002

Table 1: Conversion tools to prepare for parsing. See also TOM Conversion Service, http://tom.cs.cmu.edu/.

in Automatic extraction of reference linking information from online documents
by Donna Bergmark 2000
Cited by 11

Table 1. Credentialsmay have optionalconditionsassociated with the granted rights. Assume the following credentials are stored in the security context associated with the user Tom.

in Representation and Evaluation of Security Policies for Distributed System Services
by Tatyana Ryutov, Clifford Neuman 2000
Cited by 30

Table 4. Same as Table 3 but for October 1997 in Figure 11 Latitudes TOMS/MLS-Model RMS r

in Tropospheric Ozone At Tropical and Middle Latitudes Derived From
by Toms Mls Residual, S. Chandra, J. R. Ziemke, R. V. Martin
Cited by 3

Table 5. Same as Table 3 but for February 1997 in Figure 12 Latitudes TOMS/MLS-Model RMS r

in Tropospheric Ozone At Tropical and Middle Latitudes Derived From
by Toms Mls Residual, S. Chandra, J. R. Ziemke, R. V. Martin
Cited by 3

Table 7: Results for asym family. Running time in seconds (top), # of relabel operations (bot- tom).

in Experimental evaluation of a parametric flow algorithm
by Maxim A. Babenko, Andrew V. Goldberg 2006
Cited by 3

Table 3. Average Precision and Recall (Top); Overall Averages for Quadtree Heuristic (Bot- tom)

in Taghva method for calculating term similarity on large document collections
by Wolfgang W. Bein, Jeffrey S. Coombs, Kazem Taghva
"... In PAGE 4: ... In the 11-point display, the precision represents the max- imum precision achieved within a given recall range. For example, in the first row of the top part of Table3 , within the range of 0% a157 recall a140 10%, 55.55% was the average per- centage of the maximum precision achieved in this range.... ..."
Cited by 1
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