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Table 6: Comparison of the number and percentage of tenders in the small pool

in unknown title
by unknown authors 2005
"... In PAGE 4: ...Table 1: Grant area achievements (hectares) Table 2: Species and areas (hectares) established under grant from 1 July 1993 to 30 June 2004 Table 3: Relative product prices for forestry and pastoral agriculture Table 4: Differences between areas established and accepted (hectares) Table 5: Reasons for the difference between the approved and established area Table6 : Comparison of the number and percentage of tenders in each pool Table 7: Project grants and expenditure (GST inclusive) Photo 1: Large eroding gully on Ihungia Station west of Te Puia prior to planting Photo2: The same area as in Photo 1 six years after planting. This illustrates how quickly forest cover can be established and erosion contained Photo 3: Spot (release) spraying around newly planted Pinus radiata on Tauwhareparae Properties (ex Port Gisborne Limited).... ..."

Table 2. Error rate (%) of the classifler with difierent pooling and length parameters. Pooling

in Appearance-Based Recognition of Words in
by American Sign Language, Morteza Zahedi, Daniel Keysers, Hermann Ney 2005
"... In PAGE 6: ... 5 Experimental Results First, we choose the down-sampled original image after skin intensity threshold- ing and employ the HMM classifler to classify words of the database. The re- sults of this classiflcation using the Gaussian distribution with difierent sequence lengths and pooling are shown in Table2 . Using word-dependent pooling gives better results than state-dependent pooling or density-dependent estimation of the variances.... In PAGE 6: ... We employ an HMM of each word with the length of the minimum and aver- age sequence length of the training samples. As it is shown in Table2 , neglecting other parameters, the shorter HMMs give better results. This may be due to the fact that the database is small and if the HMM has fewer states, the parameters of the distribution functions will be estimated better.... ..."
Cited by 3

Table 1. It is natural to conjecture that

in Asymptotic Behavior of Excitable Cellular Automata
by Richard Durrett, David Griffeath 1993
"... In PAGE 13: .... See also Remark 4.3. We conclude this discussion of experimental nd- ings with some speculative curve- tting. By study- ing trajectories of band tests such as those shown in Figure 6 for systems with larger ranges, we have extended Table1 to all 40. Evaluation of the exact cuto becomes increasingly delicate as in- creases, so there may well be some small errors in our numerical results.... ..."
Cited by 2

Table 1: Small disconnected natural numbers and their Haar Graphs. For de - nition of b, see Proposition 4.1.

in Cyclic Haar Graphs
by M. Hladnik, D. Marusic, T. Pisanski

Table 9: Accessing the function pool This small tool is usable for a group of students and a teacher working together on a small problem (APL function). Imagine the following scenario: A teacher sets up a task for his/her students. The rst user that has assembled an APL function to perform the speci ed task puts it into the function pool. Before the teacher can put another task into the pool, all other users have to install the function in the pool in their respective workspaces with the GET command

in Extending the Two-Partner Shared Variable Protocol to n Partners
by Thomas Kolarik

Table6. Linear models for chewing damage caused by folivorous insects on manzanitas. The sign of the regression coefficients for all habitat, host-plant, and pubescence variables indicates the nature of the association with the response variable. Blank entries in the table indicate that no pubescence traits were retained in the model. See Table2 for definitions of abbreviations.

in pubescence on the folivorous insects
by Melissa R. Andres

Table 1: Pooled confusion matrix for experiment I with natural (top) and plf (bottom). Stimuli are given in the columns. nat b m v d n l z Z g

in Audiovisual Perceptual Evaluation of Resynthesised Speech Movements
by Matthias Odisio Erard, Matthias Odisio, Gérard Bailly
"... In PAGE 2: ... Dispersion of the incorrect responses is greater with plf than with natural. However, the structure remains the same; a sketch of this degradation is given in Table1 . Salient properties of these results are: the poor salience of [z], the loss of the salience of [Z] in rounded context and the salience of nasal consonants ([m] and [n] are never confused with [b] or [d]).... ..."
Cited by 1

Table 4. Summary of large natural scene experiment. The training images were drawn at random from the pool of available images, with the remaining images serving as a disjoint set of test images.

in Hierarchical Discriminant Analysis for Image Retrieval
by Daniel L. Swets, John (Juyang) Weng 1999
Cited by 32

Table 1 Power of DNA pooling strategy compared to individual genotyping

in ORIGINAL ARTICLE
by S Shifman, A Bhomra, S Smiley, Nr Wray, Mr James, Ng Martin, Jm Hettema, Pe Slagboom, J Flint
"... In PAGE 4: ... We calculated the power using different effect sizes of OR between 1.2 and 3 ( Table1 ). For small effect sizes, that is, ORs of 1.... ..."

Table 2. Summary of large natural scene experiment. The training images were drawn at random from the pool of available images, with the remaining images serving as a disjoint set of test images.

in SHOSLIF-O: SHOSLIF for Object Recognition and Image Retrieval (Phase II)
by Daniel L. Swets, John J. Weng 1995
"... In PAGE 19: ... Following training, the system was tested using a disjoint test set. A summary of the makeup of the test and the results are shown in Table2 . The instances where the retrieval failed were due... ..."
Cited by 6
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