Results

**1 - 4**of**4**### Table 2 : Agent-based modelling platforms

2005

"... In PAGE 5: ...1. Choosing an ABM platform Even though there has been a range of tools designed to help build ABMs (see Table2 for a list of example ABM platforms), there is still much design and development work (Gilbert amp; Terna 1999; Gilbert amp; Bankes 2002). Readers interested in a more comprehensive list of platforms are urged to acces the appendix in Tobias and Hofmann (2004).... ..."

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### Table 2 Results of Forecasting Turning Points in the Median Output Growth Rate of 18 Countries: 1980-1995. Number of Correct Forecasts for Alternative Models

"... In PAGE 4: ...hen the optimal forecast is NDT. Similar considerations relate to forecasting UTs and NUTs. See LeSage (1996), Zellner, Hong and Min (1991) and Zellner, Tobias and Ryu (1997) for further discussion and applications of this turning point forecasting methodology. In Table2 are the number of DT, NDT, UT and NUT events that actually occurred in our sample and the number of correct forecasts using the procedure described above with each of our three 3We use the forecasted median from the alternative models as an approximation to the posterior predictive mean of wT+1, and assume the predictive density is symmetric about the forecasted median.... ..."

### Table 4: 80% System utilization (the number in parenthesis is the average number of memory bu ers required per request migration)

"... In PAGE 15: ... Tables 2 and 3 present the number of replicas constructed per object by the divisor technique of Figure 5b for WWW-Tobias and exponential distribution, respectively. Table4 presents both the analytical and experimental results for each access pattern with 80% system utilization. In these experiments, Mitra rejected 0% of requests (the analytical models pre- dicted 0.... In PAGE 17: ...6% utilization, exponential distribution of replication and migration (compare rows ve and seven). The reasoning for this is di erent than that of Table4 . With a high system load, when request migration requires additional disk bandwidth when migrating a request, if a new request arrives during the time period that Mitra is performing a migration, the rst block of secondary copies of the referenced object might be rendered unavailable due to migration.... ..."

### Table 1 Performance of three algorithms for several gradient-domain compositing problems. For each dataset, we show the number of megapixels, the number of variables per color channel in the reduced linear system as a percentage of the total number of pixels, and the error between the solutions computed using the reduced and full linear sys- tems (error is measured using the 8-bit red channel, with both an average per-pixel RMS error and the maximum error across all pixels). We show the time and memory performance of three algorithms: quadtree-based (QT), hierarchical basis preconditioning (HB), and locally adapted hier- archical basis preconditioning (LHB). Each panorama was stitched from five source images.

"... In PAGE 1: ... (Fifth row) The result computed in this reduced space, which can be computed much more efficiently, is vi- sually identical to the full gradient-domain solution. The numerical error is shown in Table1 . Images courtesy of Tobias Oberlies.... In PAGE 4: ...46 9 118 112 Table 2 Performance of quadtree-based gradient-domain compositing for several very large panoramas. 4 Experimental results We compare the performance of our technique against our imple- mentation of two other algorithms for several datasets of different sizes ( Table1 ), and show several results that were too large to com- pute in available memory using other algorithms (Table 2). Most of our results are panoramas whose seams were computed using hi- erarchical graph cuts [Agarwala et al.... In PAGE 4: ... Most of our results are panoramas whose seams were computed using hi- erarchical graph cuts [Agarwala et al. 2005], though the first result in Table1 demonstrates image region copy-and paste with manu- ally chosen seams. In the interest of space, most of our results can only be seen on the project web site, although the Rainier dataset is shown in Figure 1.... In PAGE 4: ... Even when we scale the computed offsets by ten to generate the visualization in the third row of Figure 1, no differences are visible. The error values in Table1 explain why. For color values that range from 0 to 255, the per-pixel RMS error is in the hundredths.... ..."

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