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Table 2: The running time comparisons of Burns apos;, KO, YTO, Howard apos;s, HO, Karp apos;s, DG, Lawler apos;s, Karp2, and OA1 algorithms on the random graphs with n nodes and m arcs. For the cases marked with N/A, either we could not get a result in a day, or we ran out of memory because of the quadratic space complexity of the algorithm in context.
Table IX. Direct Mapping for Query 4
Cited by 1
Table 2 We now present the formal definition of multivalued (We give the definition in Beeri, Fagin, dependencies. and Howard1, which is slightly more general than the definition in Fagin7, in that the left- and right-hand sides of the multivalued dependency need not be disjoint.) Let R be a relation. the column names of R, and u is a tuple of R, then by u[X] we mean the projection of u onto X. When we say that x is an X-value of the relation R, we mean that x=u[X] for some tuple u of R. Let X and Y be subsets of the column names of R. Define
1977
"... In PAGE 4: ... this set is a function of x alone and does not depend on the z-values that appear with x. T(EMPLOYEE,CHILD,SALARY,YEAR) in Table2 . The multivalued dependency EMPLOYEE%HILD holds for T, since, for example, CHILDT(Gauss) equals both CHILDT(Gauss, $4OK, 1975) and CHILDT(Gauss, $5OK,1976), which all equal {Gwendolyn,Greta).... In PAGE 4: ... multivalued dependencies provide a necessary and sufficient condition for a relation to be decomposable into two of its projections without loss of information (in the usual sense that the original relation is guaranteed to be in the natural join of the two projections). EMPLOYEEWHILD holds for the relation T(EMPLOYEE,CHILD,SALARY,YEAR) in Table2 , it follows that this relation can be decomposed into the two relations T1(EMPLOYEE,CHILD) and Tq(EMPLOYEE,SALARY,YEAR) without loss of information (see Table 3). We note that T(EMPLOYEE,CHILD,SALARY,YEAR) cannot be decomposed on the basis of any functional dependencies, because there are none (except trivial functional dependencies, such as A+A).... ..."
Cited by 5
Table IV. Direct Mapping for Query 2
Cited by 1
Table 3: Racial Profile of Columbia Schools
2001
Table 1. Sources, 16S rDNA accession numbers and references for strains and 16S rDNA sequences used in the study ................................................................................................................................................................................................................................................................................................................. Culture collections are abbreviated as: Bangor, A. J. Howard, Ysbyty Gwynedd, Bangor LL57 2PW, UK; CCUG, Dept of Clinical Microbiology, University of Go$ teborg, Go$ teborg, Sweden; CDC, Centers for Disease Prevention and Control, Atlanta, GA, USA; FDC, Forsyth Dental Center, Boston, MA, USA; LCDC, Laboratory Centre for Disease Control, Ottawa, Canada K1A 0L2; NCTC, L. R. Hill, National Collection of Type Cultures, London NW9 5EQ, UK; NRL, Neisseria Reference Laboratory, US Public Health Service Hospital, Seattle, WA 98114, USA.
"... In PAGE 3: ... Table1 (cont.) Strain Accession no.... In PAGE 3: ..., 1978). It consisted of many members of the Neisseriaceae ( Table1 ) and 20 members of the c- and b-Proteobacteria, which served as outgroup taxa. For likelihood, an alignment was initially analysed using dnapars (Felsenstein, 1993) and macclade (Maddison amp; Maddison, 1992) to determine empirically the transition to transversion (Ts}Tv) ratio and nucleotide base frequencies.... ..."
Table 1. Relation Written Back to API
1994
"... In PAGE 18: ...EXPANSE Software for Distributed Call and Connection Control Howard Bussey The application modifies this local copy and writes the table shown in Table1 back to the API. The changed objects are highlighted.... ..."
Cited by 3
Table 3: Regression Results
"... In PAGE 18: ... In neither the Howard or Calvert models was evidence of spatial correlation found. The significance of certain variables, the overall fit, and the evidence of spatial correlation varied by county ( Table3 ).... ..."
Table 7.2 lists various file system settings. Reiserfs and SGI XFS were not created and mounted with default settings because the default settings for those two file systems assume memory as a scarce resource. Section 7.1.1 will detail those non-default options. Although the most widely used benchmark in the file-system literature is the Andrew File System Benchmark [Howard et al. 1988], that benchmark no longer stresses modern file systems because its data set is too small. The chosen benchmarks for this study are the Sprite LFS microbenchmarks [Rosenblum and Ousterhout 1991] with slight modifications (Section 7.1.2), the PostMark macrobenchmark1 [Katcher 1997], and a revised version of PostMark that will be described in Section 7.3. All results are presented at a 90% confidence level. The details of individual benchmark experiments will be discussed in corresponding subsections.
TABLE 2. Detailed results. Sizes of compressed files (in bytes) and compression ratios for various algorithms. For each combination of image number, resolution and algorithm, two numbers are shown. The top number (roman type) is the byte count, including overhead. The bottom number (italic type) is the compression ratio, that is, the ratio of the original file size (with no overhead) to the compressed file size (including overhead). mgtic was unable to compress some images
1997
"... In PAGE 9: ... G. HOWARD TABLE2 . Continued Lossless Lossy Image Resolution SPM G3 G4 JBIG mgtic SPM mgtic 7 200 38798 78563 66434 52261 45368 25967 24794 13.... ..."
Cited by 33
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