### Table 1: Efficiency comparison for CCA-secure public-key encryption schemes Scheme

2006

### Table 3. Effects of conjunctive-type predicate de- fines on speedup and instruction count.

1999

"... In PAGE 10: ... The final experiment examines the effectiveness of the new predicate types (conjunctive and disjunctive, described in Section 2) in the context of Boolean minimization and justifies the need for the proposed architectural extensions. Table3 presents... ..."

Cited by 10

### Table 3. Effects of conjunctive-type predicate de- fines on speedup and instruction count.

1999

"... In PAGE 10: ... The final experiment examines the effectiveness of the new predicate types (conjunctive and disjunctive, described in Section 2) in the context of Boolean minimization and justifies the need for the proposed architectural extensions. Table3 presents... ..."

Cited by 10

### Table 3. Conjunctions of query predicates that yield empty results when their reference objects are the same O: Yield Empty Result

"... In PAGE 9: ... The complete set of contradictory conjunctions of join conditions and the simplification rules for conjunctions and disjunctions of join conditions can be easily derived from the corresponding set and algorithm in Section 3.1 by replacing the query regions q1 and q2 with s as shown in Table3 . Also, as discussed in Section 3.... ..."

### Table 7: Criterion 4

"... In PAGE 18: ...ive clause Pi (i =1..n) with Sc as false,evaluateeachQj (j =1..m) as false at least once, respectively. Table7 illustrates the idea of this criterion. Since evaluating Pi as true requires that all the conjunctive clauses Q1,Q2, .... ..."

### Table 3: Security Levels and Encrypted Data Security Encrypted Field

1994

"... In PAGE 4: ... Amount of data encrypted depends on the selected se- curity level. Table3 shows correspondence between the security levels and encrypted fields of a datagram. Boxes with 14 denotes encrypted data, and (auth) denotes that the field is encrypted into an appropriate authenticator format.... ..."

Cited by 2

### Table 2 represents the real{valued activations of a disjunctive neuron for binary input values. Just as in the case of the conjunction, Figure 3 shows the similarity between a neural disjunction (c) and the common fuzzy operators maximum (a) and algebraic sum (b). 2.5 DNF{ and CNF{networks Since any quanti er{free logical formula can be represented in conjunctive reps. disjunctive normal form (see [8], p.19 ), we introduce a network architecture that is structured like such a formula in normal form. We will call this general form a logical normal form network (LNF{network) to summarize conjunctive and disjunctive normal form networks (CNF{ and DNF{networks).

"... In PAGE 5: ...99 1 1 1 0.99 Table2 : Neural activation ai for weights w1i = w2i = 20 and threshold i = 15 to represent a neural disjunction. 0 0.... ..."