### Table 1 Summary of different attributes across various related work Work Active cameras Multiple Interaction Model Dynamic Interact

2006

"... In PAGE 3: ... Thus the aim of this paper is to provide a generalized framework which employs coo- petitive interaction and MPC feedback and describe detailed experimentation results for the same. A summary of related work has been shown in Table1 . It clearly highlights the attributes of visual surveillance which have already been adopted by the research community and also those which have been proposed for the first time in this paper.... In PAGE 3: ... It clearly highlights the attributes of visual surveillance which have already been adopted by the research community and also those which have been proposed for the first time in this paper. As can be seen in Table1 , a significant amount of work has already been done using multiple active cameras. Inter- action between cameras is also commonly described, but the coopetitive approach of interaction between cameras for global optimization has been introduced for the first time in our proposed framework.... ..."

### TABLE 2. Substrate and kinase interaction domains found on multiple proteins

### Table 5. Summary of the analyses in the different decay channels for deep inelastic and low multiplicity interactions. The data sample used, the expected background, the number of events observed in the data and N are given for each decay channel.

### Table 3: Multiple Regression Analysis Predicting Interaction in Synchronous Versus Asynchronous Discussions

"... In PAGE 5: ...7, p lt; .0001 ( Table3 ). The mean sentence per person in synchronous mode is 26.... ..."

### Table 2: For the k and pb choices indicated in the side margin, the interactions between certain variants of each predictor listed in the top margin were investigated in a complete two-way factorial search. Thus, the two-way multiplicative interactions between all possible pairs of entries in this table were correlated with ideal strike limits. For `biological quantities apos;, all four of MSYR, MSYL, MSY, and RY were used.

"... In PAGE 10: ... Among both sets, the selection also focussed on maintaining a diverse list of potential predictors. By sifting through the results in this manner, a list of 128 potential predictors was iden- ti ed for closer examination of interactions; these are listed in Table2 . The new predictors consisting of all two-way multiplicative interactions between those listed in Table 2 were examined.... In PAGE 10: ... By sifting through the results in this manner, a list of 128 potential predictors was iden- ti ed for closer examination of interactions; these are listed in Table 2. The new predictors consisting of all two-way multiplicative interactions between those listed in Table2 were examined. Excluding those interactions already considered as part of Table 1, that amounts to another 8,128 potential predictors, for a total of 36,564 predictors that one might use to nd an optimal SLA.... In PAGE 17: ... Within each block, the results from all possible combinations of parameter values were correlated with ideal strike limits, as were the results from all two-way multiplicative interactions except for those involving the italicized parameter value entries. Table2 shows which between-block interactions were examined.... ..."

### Table 1: Classification of extraction methods. Some methods are durable, which means, that the method manipulates the model at multiple times during a sequence of interactions.

in Object-Oriented Modeling For The Extraction Of Geometry, Texture And Reflectance From Digital Images

"... In PAGE 4: ... For the object-oriented model of the different methods, we need a classification of the significant properties. Table1 shows the different extraction methods and the properties, which are rel- evant for the object-oriented model. The methods are interactive, automatic or semi-automatic.... ..."

### Table 1: Summary of predictor variables examined during correlation search strategy. Within each block, the results from all possible combinations of parameter values were correlated with ideal strike limits, as were the results from all two-way multiplicative interactions except for those involving the italicized parameter value entries. Table 2 shows which between-block interactions were examined.

"... In PAGE 9: ... Many di erent versions of these potential predictors were considered by varying the values of k, pb, qpb 1 , qpb 2 , qbio, qwg, 1, 2, and 3. Table1 lists the values of these parameters used to generate each potential predictor. Within each block of this table, a full factorial crossing of relevant parameters (i.... In PAGE 9: ...f relevant parameters (i.e. all possible combinations), and all possible multiplicative two- way interactions except those involving italicised entries, were used to generate potential predictors. Thus, for example, the rst block of Table1 describes 3 4 2 + 242 = 300 possible predictors Yi. Table 1 therefore lists 28,436 potential predictors overall.... In PAGE 9: ... Thus, for example, the rst block of Table 1 describes 3 4 2 + 242 = 300 possible predictors Yi. Table1 therefore lists 28,436 potential predictors overall. To consider all possible multiplicative two-way interactions between blocks would raise the total number of potential predictor variables to 11,103,828.... In PAGE 10: ...WMP simulation software can be found at www.colostate.edu/ geof/iwcawmp.html. Selecting predictors and a model class This section describes the process by which a subset of predictors, Y, and a model class, g(Y; ), were selected. Table1 lists 28,436 potential predictors, and we would like to add to that list all 11 million potential predictors arising from two-way multiplicative interactions. Without computing all of these, we would like to examine the available 28,436 predictors listed in Table 1 to look for hints about which ones might be involved in useful interactions.... In PAGE 10: ... Table 1 lists 28,436 potential predictors, and we would like to add to that list all 11 million potential predictors arising from two-way multiplicative interactions. Without computing all of these, we would like to examine the available 28,436 predictors listed in Table1 to look for hints about which ones might be involved in useful interactions. To limit computational e ort, only a single investigative measure was used: the sample correlation of each of the 28,436 predictors with the ideal strike limits2, pooled across the B3 and B7 trials.... In PAGE 10: ... The new predictors consisting of all two-way multiplicative interactions between those listed in Table 2 were examined. Excluding those interactions already considered as part of Table1 , that amounts to another 8,128 potential predictors, for a total of 36,564 predictors that one might use to nd an optimal SLA. This amounts to less than 0.... ..."

### Table 1: Summary of predictor variables examined during correlation search strategy. Within each block, the results from all possible combinations of parameter values were correlated with ideal strike limits, as were the results from all two-way multiplicative interactions except for those involving the italicized parameter value entries. Table 2 shows which between-block interactions were examined.

1999

"... In PAGE 7: ... Many di erent versions of these predictors were considered by varying the values of k, pb, qpb 1 , qpb 2 , qbio, qwg, 1, 2, and 3. Table1 lists the values of these parameters used to generate each predictor. Within each block of this table, a full factorial crossing of relevant parameters (i.... In PAGE 7: ...i.e. all possible combinations), and all possible multiplicative two-way interactions except those involving italicised entries, were used to generate predictors. Thus, for example, the rst block of Table1 describes 3 4 2 + 242 = 300 possible predictors Yi. Table 1 therefore lists 28,436 predictors overall.... In PAGE 8: ... Such e ort is far beyond the scope of this paper; therefore some limitations were introduced. Without computing all 11 million predictors arising from two-way multiplicative inter- actions, one would like to examine the available 28,436 predictors listed in Table1 to look for hints about which ones might be involved in useful interactions. To limit computational e ort, only a single investigative measure was used: the sample correlation of each of the 28,436 predictors with the ideal strike limits3, pooled across the B3 and B7 Initial Explo- ration Trials.... In PAGE 8: ... The new predictors consisting of all two-way multiplicative interactions between those listed in Table 2 were examined. Excluding those interactions already considered as part of Table1 , that amounts to another 8,128 potential predictors, for a total of 36,564 predictors that H-optimisation might use to nd an optimal SLA. This amounts to less than 0.... ..."

Cited by 1

### Table 1: Mean multiplicities and cross sections for resolved photon events. 3 Results and Discussion Using this version of the simulation, the e ects of multiple scattering are studied using the fol- lowing choices for the various parameters of the model, structure functions used and kinematic cuts. Pres = 1=300, which is motivated by assuming that the resolved photon interacts domi- nantly like a -meson. The minimum transverse momentum of a hard scatter, pTmin = 2:5 GeV. For the structure functions, MRS D- for the proton [14] and GRV for the photon [15] are used. A cut on the p CM energy was made, i.e. 114 GeV ps 265 GeV, similar to those usually made by the experiments. Events were generated both with and without multiple interactions. Events generated without multiple interactions are in good agreement with those generated by the unmodi ed HERWIG.

"... In PAGE 4: ...ade by the experiments. Events were generated both with and without multiple interactions. Events generated without multiple interactions are in good agreement with those generated by the unmodi ed HERWIG. Table1 shows the variation of the mean multiplicity of hard scatters (hnHi) with p CM energy, for events with at least one hard scatter. Also shown is the total hard scattering cross section, H(s).... ..."

### Table 2. Multiple Regression Analysis of BAs 17 and 37 and Age Interaction Terms on Frequency and Length Using Simultaneous Entry of Predictors

"... In PAGE 5: ... Using multiple regression with repeated measures on the scan block variable, we performed separate analyses of the word frequency and length regression coefficients obtained for each participant, in which the normalized PET counts for the local maxima in BAs 17 and 37 were simultaneous predictors.3 We also included variables representing the main effect of age group and its interaction with each of the predictors (see Table2 for coefficient and t values for each predictor). The results indicated that when the criterion variable was the standardized regression coefficient for word frequency, there was a significant main effect for age group, as well as significant interactions between age group and the normalized PET counts at both local maxima (the age interaction for BA 37 was marginally significant).... In PAGE 11: ... (2002) data indicated that the changes in rCBF activation across the three lexical conditions were minimal and were not associated with age differences. Variables representing the different lexical task conditions were initially entered simultaneously with the predictors listed in Table2 , but none of these condition variables were significant predictors. Consequently, the lexical condition variables were not included in the final analysis presented in Table 2.... ..."