### Table 4: Size and power of swap variance ratio-test in presence of market microstructure noise no noise i.i.d. noise

2005

"... In PAGE 19: ...(T )3, i.e. feasible and (approximately) valid with i.i.d. noise. Table4 reports the size (Panel A) and power (Panel B) of the SwV tests in the presence of i.... ..."

### Table 5 Maximum entropy model to predict French translation of in. Features shown here were the rst non template 1 features selected. [verb marker] denotes a morphological marker inserted to indicate the presence of a verb as the next word.

1996

"... In PAGE 22: ... The automatic feature selection algorithm rst selected a template 1 constraint for each of the translations of in seen in the sample (12 in all), thus constraining the model apos;s expected probability of each of these translations to their empirical probabilities. The next few constraints selected by the algorithm are shown in Table5 . The rst column gives the identity of the feature whose expected value is constrained; the second column gives L(S; f), the approximate increase in the model apos;s log-likelihood on the data as a result of imposing this constraint; the third column gives L(p), the log-likelihood after adjoining the feature and recomputing the model.... ..."

Cited by 614

### TABLE 5. Presence of insertions in the chromosome of different strains of E. coli

2002

Cited by 1

### Table 1. . Open network Closed network

"... In PAGE 13: ...13 Summary The best we can expect to prove is the complement of the previous counter-examples. More precisely, we propose in Table 2, a new detailed version of Table1 , with the sections where the positive results are stated. Table 2.... ..."

### Table 1: Collaborative learning in a closed vs. open group.

1998

"... In PAGE 2: ....1. An open-ended collaborative learning environment Our research focuses on open-ended collaborative learning using computers and Internet. Table1 shows several variables of collaborative learning in a closed group and in an open group. In a closed learning environment, like for instance, an ordinary classroom, a teacher organizes groups, gives the subject to the each group, and sets the time table for the discussion in advance.... ..."

Cited by 1

### Table 2 - Distributions of closed- and open- class words in a safety text

1996

"... In PAGE 5: ... Table2 comprises three groups of closed class words and one group of open class words. This categorisation is based on the value of the weirdness coefficient associated with members of each group.... ..."

Cited by 1

### Table 2. Results in the presence of a symmetric faulty node.

2007

"... In PAGE 27: ... The faulty node still behaves randomly, but its effect at the receiving nodes is identical. As shown in Table2 , the maximum available memory is used to model check this case. Due to the BDD construction, the memory usage is far more than the Byzantine faulty case.... ..."

### Table 1. A comparison between the different types of societies. Fixed Closed Semi-closed Semi-open Open Anarchic

2001

Cited by 17

### Table 1: Characteristics of special morphologies.

1999

"... In PAGE 4: ... Mohr et al. (1957) first used the striation thickness (see Table1 ), defined as one-half the spacing between layer midplanes in a lamellar structure, as a measure of mixing. Striation thickness is related to the specific area of a lamellar mixture by = 1 SV (2.... In PAGE 5: ....2.2 Example Area Tensors When the mixture has one discrete and one continuous phase, the area tensor provides information about the shape and size of the discrete-phase domains. Table1 shows the area tensors for three example mixture morphologies. The area tensor is triaxial (isotropic) for spherical domains, biaxial (transversely isotropic) for cylindrical domains, and uniaxial for lamellar structures.... In PAGE 5: ... We can then define a local characteristic length scale Lc for the discrete phase as the ratio of the total volume Vd of the discrete phase within V to the total interfacial area Sd within V Lc Vd=Sd = =SV (2.8) Table1 gives the characteristic length scales for the three example morphologies. The characteris- tic radius of the lamellar structure is related to the striation thickness by r = .... In PAGE 14: ... This approximation is generated by choosing a functional form, constraining the form, and fitting the constrained function to data generated from the exact closure. The constraints force the closure to obey geometric symmetries, give exact results in the three limiting cases of Table1 , and have correct asymptotic behavior near those limits (Wetzel and Tucker, 1997). Exact data for ^ A (1), ^ A (2), and ^ A (3) as a function of ^ A(1) and ^ A(2) were generated using Eqns.... In PAGE 22: ... (2.8) and Table1 with a dispersed-phase volume fraction = 0:10, this tensor represents a lamellar morphology with an average sheet... ..."

Cited by 1

### Table 8: Performance of word segmentation (morphological closing) with respect to (a) the ground truth; (b) the algorithm output.

"... In PAGE 10: ... As a nal step, the algorithm performs hypothesis test in the height of the detected word blocks to handle merging words among adjacent text lines. Table8 illustrates the numbers and percentages of miss, false, correct, splitting, merging and spurious detections with respect to the ground truth words as well as the algorithm output. Table 8: Performance of word segmentation (morphological closing) with respect to (a) the ground truth; (b) the algorithm output.... ..."