### Table 1: Types of self-reproduction

"... In PAGE 2: ... 1997). Three possible types of reproduction (exact replication, near replication of an ancestor, and near replication of a parent) are presented in Table1 , st being a system s produced in t-th gener- ation. The case of near replication of a parent appears to be the most distributed naturally (and also initially studied by von Neumann (Aspray amp; Burks 1987)), al- though other cases may also exist2.... ..."

### Table 1: Joint Weights for Joint-Displacement. Joint Variable Joint Weight Comments

2004

"... In PAGE 9: ... In addition, the exact values of the weights are irrelevant; they simply have to have significantly different orders of magnitude. Note that some of the weights in Table1 (used with joint displacement) are discontinuous, and this is because movement in various directions can result in different degrees of acceptability. These discontinuities can lead to computational difficulties.... ..."

Cited by 1

### Table 5: Joint Relation

1998

"... In PAGE 11: ... is: (M, Yes, B.A., IL). M comes from the gender relation, Yes and B.A. from the personal relation, and IL from travel. The transactions of R are shown as sequences in Table5 (ignore numbers and parenthesis for now). Both Apriori and AprioriTid divide the problem into two subproblems: generating frequent itemsets, and rule construction (see Section 2).... In PAGE 12: ... Now, the support of I is exactly jG(Hi(T ))j, where i = argmini(I Hi(T )). For example, Table5 contains the counts jG(Hi(T ))j for i = 1; 2. For i = 3 we always have jG(Hi(T ))j = 1, and this number is omitted.... ..."

Cited by 3

### Table 1 Joint Distribution of the Outputs of S

1995

"... In PAGE 5: ... Thus for a uniform distribution of inputs, each output in a uniform distribution of outputs would occur 4 times. Table1 (at the end of the paper) is a table of the number of times each output of the pair S 1 ;;S 2 occurred with the common key bits (0;; 0). Obviously, this distribution of outputs is non- uniform, as is the distribution of any other pair of adjacentS-boxes with anyvalue for the common key bits, and it is this fact we exploit in the cryptanalysis.... In PAGE 6: ...S X;;Y (s;; t)=#fI;;J 2 Z 6 2 j I 5 J 1 = s;; I 6 J 2 = t;; S p (I)=X;; S q (J)=Y g ;; so Table1 isatableofS X;;Y (0;; 0) for S-boxes 1 and 2, and X X;;Y S X;;Y (s;; t)=2 10 : We can de ne two more functions for the outputs of each S-box, namely d X (i;; j) = #fI 2 Z 6 2 jI 5 = i;; I 6 = j;; S p (I)=Xg;; e Y (i;; j) = #fJ 2 Z 6 2 jJ 1 = i;; J 2 = j;; S q (J)=Y g;; so d X and e Y are the number of outputs over all possible inputs of the individual S-boxes given that certain inputs are xed. Eachrow of a DES S-box is a permutation, so wehave the following properties, X i d X (i;; j)= X j e Y (i;; j) = 2 for all X;; Y 2 Z 6 2 : We can give an expression for S X;;Y in terms of the functions de ned above S X;;Y (s;; t) = P i;;j d X (i;; t j)e Y (s i;; j) = d X (0;;t)e Y (s;; 0) + d X (1;;t)e Y (s 0 ;; 0) + d X (0;;t 0 )e Y (s;; 1) + d X (1;;t 0 )e Y (s 0 ;; 1) = d X (0;;t)e Y (s;; 0) + (2 ; d X (0;;t))e Y (s 0 ;; 0) + d X (0;;t 0 )(2 ; e Y (s;; 0)) + (2 ; d X (0;;t 0 ))(2 ; e Y (s 0 ;; 0)) = 4+(d X (0;;t) ; d X (0;;t 0 ))(e Y (s;; 0) ; e Y (s 0 ;; 0)) = 4+(;1) s t (d X (0;; 0) ; d X (0;; 1))(e Y (0;; 0) ; e Y (1;; 0)) = 4+(;1) s t d X e Y ;; where d X =(d X (0;; 0) ; d X (0;; 1)), e Y =(e Y (0;; 0) ; e Y (1;; 0)), and s 0 denotes s 1, t 0 denotes t 1.... In PAGE 22: ...We can therefore calculate the distribution of the output of a pair of S-boxes given the inputs to (and hence the outputs of) the S-boxes two rounds earlier. This corresponds to perturbing the values of S X;;Y ,asgiven for example in Table1 , by a small but unknown amount, with most values of S X;;Y for most S-box pairs almost exactly correct. In order to perform the cryptanalysis, wehave to calculate Sn X;;Y ,an n-fold convolution of S X;;Y with itself.... ..."

Cited by 15

### Table 1: specifications, and to hinge joint, location.

"... In PAGE 5: ..., similar to the case of a ball joint, except that the axes will not all in- tmersectl. Second, the fixed parameters that were used in Table1 may not be exact. We plan to employ open-loop calibration [l] to check on these parameters and to vcr- ify the closed-loop results.... ..."

### Table 1_ Social Support Networks in Reproductive Units as Conditioned by Nating and Transfer Patterns among Primates

in Nodal Notes

"... In PAGE 39: ... Tables 1 and 2 show the contrast between data. Table1 is a standard cross classification, Religion by Party, while Table 2 is a friendship relation. Table 1-shows frequencies : The quot;4 quot; at the upper left indicates that four people were cross-classified as both Strong Democrats and as Episcopalians .... In PAGE 39: ... Table 1 is a standard cross classification, Religion by Party, while Table 2 is a friendship relation. Table1 -shows frequencies : The quot;4 quot; at the upper left indicates that four people were cross-classified as both Strong Democrats and as Episcopalians . Table 2 shows answers, yes or no: quot;F apos; in Allen apos;s row and Taylor apos;s column says quot;Yes quot;, these two men were friends .... In PAGE 39: ... Table 2 shows answers, yes or no: quot;F apos; in Allen apos;s row and Taylor apos;s column says quot;Yes quot;, these two men were friends . Table1 represents data for 1052 people while Table 2 represents data for exactly nine men . Table laggregates people into categories, using two variables, while Table 2 uses no aggregation and no variables.... In PAGE 40: ...Table1 . Standard Cross-Classification, Party Identification by Religion From the General Social Survey, N.... In PAGE 57: ... This pattern will eventually permit the identification of a23, a24 and a25 as a unanimous vote by W(N), W(O) and E. The Structure of the Narrative is depicted in the Appendix - Table1 . It now remains to be seen how it can be abstracted with a view to generalisation.... In PAGE 66: ...Table1 . Abstraction of Structure : Case I (Interactive Mode - Equivalence Classes) domain a6W(O) a7W(M W(O) a9w(N) a12c a13W(O) aiaW(N) a15w(o) a16E al4w(o) C2BR Caw(O)w(N) C6CEW(N)w(O) C C CMw(o) 4 a19 - a20M a21w apos;(0) a22M 66 mapping range description of abstract action CiM Manager makes finan- cial proposals to restrict dividends External interests mobilise to support M C3CE External members mobilise C to chall- enge M at an assembly.... ..."

### Table 2. Exact bit rate of test images.

1998

"... In PAGE 32: ...3) where P(si;cj) is the joint probability of value si and context cj and P (sijcj) is the conditional probability of value si given context cj. The results are tabulated in Table2 . The numbers are derived from compressed le sizes.... ..."

Cited by 188

### Table 4 : Estimates of covariance components and the genetic parameters derived from them, from bivariate analyses of male reproductive traits (trait 1) and days to calving (trait 2).

"... In PAGE 7: ... In the meantime, judicious inspection of results and restarting the search procedure at the maximum appear to be reasonable safeguard procedures. Results and Discussion Male and Female Reproductive Traits Results from joint analyses of male (scrotal circumference and serving capacity) and female (days to calv- ing) reproductive performance are summarized in Table4 . Overall there was very close agreement with estimates of variance components and, consequently, heritabilities (h2) and repeatabilities from univariate analyses (c.... ..."

### Table 6: Reproductive and non-reproductive effects in reptiles and amphibians

1999

### Table 8: Reproductive and non-reproductive effects in invertebrates

1999