### Table 1. A comparision of on-line and off-line sequential SFM approaches

2006

"... In PAGE 2: ... We pro- pose ways of improving the robustness of tracking by both using constraints from the partial structure and acquiring a better template when needed thus focus- ing on developing an on-line system and eliminating the need to do ransac at every step. Table1 shows the main di erences between o -line and on-line SFM... ..."

Cited by 1

### Table 3. Instructor responsibilities in on-line project-based learning

"... In PAGE 9: ... The outcome of this research was the development of guidelines for the use of instructors and students in defining their roles and responsibilities in Web-based courses. The instructor apos;s responsibilities ( Table3 ) are separated into three categories: before, during, and after the semester. Similarly, student apos;s responsibilities (Table 4) are categorized as the semester begins, during the semester, and at the end of the semester.... ..."

### Table 1: On-line computational cost of the congruence transformation across a revolute joint.

1995

"... In PAGE 7: ... The result of the z-axial congruence transformation is used in the x-axial transformation which has exactly the same form. Table1 lists the nine steps that are identi ed in each axial screw congruence transformation which leads to a particularly e cient procedure. This approach is di erent from previous approaches for transformation of spatial (and Composite Rigid-Body) inertia matrices by Lilly and Orin [4] and re ected AB inertia matrices in both the rst draft of this paper and the work of Brandl, Johanni, and Otter [2].... In PAGE 7: ... Then only successive planar rotations were applied to the terms of the form, RT NR, to achieve a certain level of e ciency. At rst this seems more e cient since it results in only one set of nine steps from Table1 . However, it leads to more computation because iRi?1 and i?1pi are much more complex than that of either Rz; i and pz or Rx; i and px in the successive axial screw approach developed in this paper.... In PAGE 11: ... (13). To accomplish this, the results of Steps Bz, Fz, and Gz must be added together as shown in Table1 : Bz + Fz + Gz + GT z . The resulting matrix, Nz 11, is symmetric with a zero row and column (the third); therefore, the three upper triangular elements of the result are needed.... In PAGE 14: ... This step nishes the computation required for the upper left 3 3 block of the complete congruence transformation. To accomplish this, the results of Steps Bx, Fx, and Gx must be added together as shown in Table1 . The resulting matrix is symmetric; therefore, only the six upper triangular elements of the result are needed.... ..."

Cited by 9

### Table 1: On-line newspapers for initial experiments

1999

"... In PAGE 15: ...2 Initial Experiments In order to determine the certainty factors for the individual heuristics, we considered two application areas: obituaries and car advertisements. To achieve geographical diversity (and thus hopefully a reasonable sampling of di erent kinds of Web documents), we chose ten on-line newspaper sites (listed in Table1 ) located in di erent regions of the United States. For each application, we retrieved ve Web documents from one site.... In PAGE 19: ... Two of the sets were documents for obituaries and car advertisements. These test documents, however, were from entirely di erent sites (compare Table1 with the site listings in Table 6 and Table 7). The other two sets were for two entirely di erent applications, namely computer job advertisements and university course descriptions (see the site listings in Table 8 and Table 9).... In PAGE 21: ...Success Rate OM 80% RP 75% SD 65% IT 95% HT 45% ORSIH 100% Table1 0: Success rates of individual heuristics and ORSIH for experimental Web documents heuristics had a 100% success rate, the success rate for our combined heuristic approach is 100%. 7 Concluding Remarks We have described a heuristic approach to discovering record boundaries in unstructured Web documents containing multiple records of interest separated by one (or more) tags.... ..."

Cited by 82

### Table 1: On-line newspapers for initial experiments

1999

"... In PAGE 15: ...2 Initial Experiments In order to determine the certainty factors for the individual heuristics, we considered two application areas: obituaries and car advertisements. Toachieve geographical diversity #28and thus hopefully a reasonable sampling of di#0Berent kinds of Web documents#29, wechose ten on-line newspaper sites #28listed in Table1 #29 located in di#0Berent regions of the United States. For each application, we retrieved #0CveWeb documents from one site.... In PAGE 19: ... Two of the sets were documents for obituaries and car advertisements. These test documents, however, were from entirely di#0Berent sites #28compare Table1 with the site listings in Table 6 and Table 7#29. The other two sets were for twoentirely di#0Berent applications, namely computer job advertisements and university course descriptions #28see the site listings in Table 8 and Table 9#29.... In PAGE 21: ...Success Rate OM 80#25 RP 75#25 SD 65#25 IT 95#25 HT 45#25 ORSIH 100#25 Table1 0: Success rates of individual heuristics and ORSIH for experimental Web documents heuristics had a 100#25 success rate, the success rate for our combined heuristic approachis 100#25. 7 Concluding Remarks Wehave described a heuristic approach to discovering record boundaries in unstructured Web documents containing multiple records of interest separated by one #28or more#29 tags.... ..."

Cited by 82

### Table 1: On-line newspapers for initial experiments

"... In PAGE 10: ... Two of the sets were documents for obituaries and car advertisements. These test documents, however, were from entirely dif- ferent sites #28compare Table1 with the site listings in Table 6 and Table 7#29. The other two sets were for two entirely di#0Berent applications, namely computer job ad- vertisements and university course descriptions #28see the site listings in Table 8 and Table 9#29.... ..."

### Table 1: Number of parameters to be updated on-line.

in Comparison of Different Growing Radial Basis Functions Algorithms for Control Systems Applications

"... In PAGE 3: ...3. NNs Architecture Comparison In Table1 a schematic comparison of the analyzed classes of SGNNs is shown. The comparison is made in terms of the number of parameters that the algorithm needs to update at each learning step.... ..."

### Table 2. Centralized vs. Decentralized On-line Monitoring.

"... In PAGE 6: ... The comparison between the centralized approach and the distributed one has been performed measuring: Bsize, the average size (number of nodes) of the belief state that the monitoring agent (centralized or distributed) needs to maintain; #States, the average number of alternative states encoded within a belief state; CPU-time, the average CPU time in msec spent for monitoring at each time instant. Table2 shows how the two ap- proaches behave w.... ..."

### Table 1: Signal objects de ned in SignalProcessing`Support`. For the syntax of CPulse, Dirichlet, FIR, IIR, LineImpulse and Pulse, consult the on-line documentation (e.g., ?CPulse).

"... In PAGE 5: ... We now examine them in more detail. Table1 lists the twelve new functions. There are discrete and continuous versions of the impulse (Impulse and Delta), step (Step and CStep), and pulse functions (Pulse and CPulse).... In PAGE 8: ... (However, certain obvious simpli cations are carried out: for example, InvZ[z,n][Z[n,z][f]] reduces to f.) Similarly, the functions of in Table1 are not reduced to Mathematica built-in objects until they appear as arguments to TheFunction. One may wish to reduce them, for example, in order to use Mathematica apos;s built-in plotting routines to plot them.... In PAGE 8: ... One may wish to reduce them, for example, in order to use Mathematica apos;s built-in plotting routines to plot them. Naturally, some functions in Table1 , like Delta and Unit, cannot be expressed in terms of Mathematica built-in objects, so TheFunction leaves them alone. Other Features Another facility provided by SignalProcessing`Support` is the plotting of signals and transforms.... In PAGE 18: ... Transforms of exponentials in the time domain are inverse-transformed by the exponential property rule, not by table lookup. Some strategies for inverting z-transforms ( Table1 0) are similar to those applied in taking forward z-transforms, but some new ones are also needed. Two such strategies are partial fractions and power series expansion.... In PAGE 19: ... complex cepstrum: Z?1flog X(z)g ! ? 1 nZ?1 ( z X(z) d dz X(z)) *9. apply the inverse z-transform to the rst N terms of a series expansion about z = 0 Table1 0: Strategies for inverse z-transforms. An asterisk means that once the rule is applied to an expression, it will no longer be applied to any part of that expression.... In PAGE 33: ...designing/analyzing 1-D analog lters DTFT discrete Fourier analysis EducationalTool interactive version of a conference paper describ- ing educational impact of Mathematica LaPlaceTest testing procedure for Laplace transforms PiecewiseConvolution tutorial on discrete/continuous convolution README brief introduction SignalProcessingExamples interactive version of paper in the The Mathemat- ica Journal SignalProcessingIntroduction introduction to Mathematica, signal processing, and the signal processing packages SignalProcessingUsage usage information about every new object de ned by the signal processing packages zTransformI z-transform tutorial, part I zTransformII z-transform tutorial, part II zTransformIII z-transform tutorial, part III Table1 1: List of the signal processing Notebooks transforms as long as the options are set properly. The default options are biased toward DTFT apos;s: Domain - gt; Continuous, DomainScale - gt; Linear, MagRangeScale - gt; Linear, PhaseRangeScale - gt; Degree, and PlotRange - gt; All.... In PAGE 40: ...Possible Values Meaning Apart Rational, All Partial fraction decomposition only applies to polynomials with real or rational coe cients Definition True, False Use the transform de nition if all else fails to nd the transform (does not apply to the inverse z or Laplace transforms) Dialogue False, True, All Ascending levels of justi cation Simplify True, False Apply SPSimplify to result Terms False or integer Number of terms in series expansion (False means none) TransformLookup list of rules Users can specify their own transform pairs, like {x[n] : gt; X[z]} or {y[t1,t2] : gt; Y[s1,s2]} Table1 2: Meaning of the Options for the Transform Rule Bases... In PAGE 41: ...Option Default Value CTFTransform Dialogue False Simplify True DFTransform Dialogue False InvDFTransform Dialogue False Terms False DTFTransform Dialogue False LaPlace Dialogue True Simplify True InvCTFTransform Apart Rational Dialogue False Simplify True Terms False InvDTFTransform Dialogue False Terms False InvLaPlace Apart Rational Dialogue True Simplify True Terms 10 InvZTransform Dialogue True Terms 10 ZTransform Dialogue True Table1 3: Options for the Transform Rule Bases. Definition always defaults to False and TransformLookup always defaults to an empty list.... ..."

### Table 5.4 On-line support tools compliance to Usability Heuristics 48

2004