### Table 2. Parameters of the local models obtained by different identification method.

### Table 2. Average recognition sensitivity for PSSMs based on seed alignments calculated by different methods, for seed alignments with different gap content

2001

"... In PAGE 8: ... Indeed, in situations where the seed alignment is constructed from dif- ferent subfamilies, sequence motifs common to a subset of neighbors but not present in the test-set domain can only be aligned correctly using multiple alignment tools. To examine the effect of gap content on PSSM recogni- tion sensitivity we compare the recognition sensitivity of PSSMs derived from alignments with approximately the same fraction of gaps, as shown in Table2 . Only alignments with average sequence identity below 30% are included.... In PAGE 8: ... Only alignments with average sequence identity below 30% are included. As can be seen from Table2 , seed alignments with more gaps produce less sensitive PSSMs for all alignment algorithms, presumably because the sequences in these alignments are among the most diverse. Interestingly, for seed alignments containing equal fractions of gaps, the local alignment methods perform as well as the global alignment methods, and the local-structure (VAST) method gives the most sen- sitive PSSMs.... ..."

### Table 2. FR rate and identification rate of the proposed method.

"... In PAGE 21: ... Table 1 represents the FR rate and correct recognition rate for the method of paired features for various MSth. Table2 shows the FR rate and correct recognition rate of the proposed method for various MSth. While a maximum correct recognition rate is required (minimum FA rate) in the fingerprint iden- tification system, a low FR rate is also desirable.... ..."

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### Table 7: Summary of identification methods.

"... In PAGE 5: ... EVALUATION AND COMPARISON To evaluate and compare the various identification methods, we now consider each method with respect to several characteristics: interpretation speed, accuracy, robustness, ease of implementation, and parameter setting. Table7 shows a summary of the described methods according to these characteristics. To illustrate some of the issues discussed, we utilize a sample eye-movement protocol from a task in which students encoded four equation values and performed some simple computation [see 15, 16], as shown in Figure 2.... ..."

### Table 4: BTS identification methods

"... In PAGE 3: ...s BTS, i.e. considering them as virtual BTSs. These methods for identifying BTSs depend on each protocol. Table4 points out the location standards defined by 3GPP that are involved in a 2G/2.5G-location solution, and the BTS identification methods that they allow.... In PAGE 4: ... In this kind of environment, it may be necessary to deliver the special RTD information from an SMLC1 to an SMLC1/SMLC2 (see Figure 2), by means of SMLCPP. However, it must be noted that SMLCPP only allows BTSs to be identified by means of LAC + CI (see Table4 ). Therefore, a reserved LAC + CI value should be set up in order to indicate the delivering of new non-standardized RTD measurements, even if it shows up some problems when LBSs are intended to be provided during roaming service.... ..."

### Table 1. Maximum Likelihood Estimates

2000

"... In PAGE 4: ... The rationale of this method is that it is robust, consistent, and straightforward. For a given distribution, the Maximum Likelihood Estimate (MLE) for its parameter is the mini- mum value of: log N Y i=1 f(xi; ) ! (4) Table1 lists the MLE of the parameters of the three chosen distributions. Finally, the data to be fitted out of the behavioral mod- els has to be prepared.... ..."

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### Table 4. Identification of TF binding sites by TFCC from clusters that are correlated with the seeding TF by various levels of expression similarity

2002

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### Table 4: Condition estimate for seed matrices

"... In PAGE 12: ...Figure 1: Condition estimate for seed matrices Table4 contains spectral condition number estimates for Vandermonde and column merging reduced seed matrices. Here, d denotes minimum number of zeros in any row of A 2 Rm p.... ..."

### Table 4 Mean recombination rates at genomic locations where autosomal full-length (FL) and truncated (TR) elements are found

2006

"... In PAGE 6: ... Two estimators of the recombination rate were used: RR and UCSCRR (see Materials and Methods). We first compared the local recombination rate for TR and FL elements ( Table4 ). We found that FL elements are on average in genomic regions with a lower recombination rate than TR elements and that this difference is statistically significant (Table 4).... In PAGE 6: ... We first compared the local recombination rate for TR and FL elements (Table 4). We found that FL elements are on average in genomic regions with a lower recombination rate than TR elements and that this difference is statistically significant ( Table4 ). This difference is observed for all five families and using both estimators of the recombination rate, although some comparisons are not statistically significant (Table 4).... ..."

### Table 2: Deviance and posterior summaries for the seed germination data.

1998

"... In PAGE 21: ...21 From the perspective of absolute t, comparing DS with n = 21 shows the hierarchical models are reasonable with 4B being particularly favoured. These data are also used by Lee and Nelder (1996) to illustrate their method for estimating the scaled deviance and degrees of freedom of hierarchical generalised linear models, where our model 4A corresponds to the GLMM model shown in their Table2 . Their estimate of 10.... In PAGE 21: ...) From the perspective of absolute t, comparing DS with n shows the hierarchical models are reasonable with 4A being particularly favoured. These data are also used by Lee and Nelder (1996) to illustrate their method for estimating the scaled deviance and degrees of freedom of hierarchical generalised linear models, where our model 4A corresponds to the GLMM model shown in their Table2 . Their estimate of 10.... ..."

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