### Table 3: Ranking distibution of the label obtained with the model-based approach on the validation dataset

2004

"... In PAGE 10: ... 4.3 Two-stage classification system As we can see on Table3 , after the first stage of classification the label of the data is not always in the first two classes, which justifies the choice of a dynamic number of classes in conflict. ... ..."

### Table 3 Summary of model-based time series clustering algorithms Paper Variable Model Model output of inter-

2005

"... In PAGE 13: ... The extracted feature vectors are then con- verted into a symbol sequence by vector quantization, which in turn is used as input for training the hidden Markov model by the expectation maximization approach. Table3 summarizes the major components used in each model-based clustering algorithm. Like feature-based meth- ods, model-based methods are capable of handling series with unequal length as well through the modeling operation.... ..."

### Table 1: Model-based segmentation and visualization

"... In PAGE 8: ... As a simple example, colors and transparencies of such objects should be selected such that contrasts are easily perceived and all relevant objects are sufficiently visible. Comparison of Model-based Segmentation and Visualization In Table1 , we compare information used for model-based segmentation and visualization. Table 1: Model-based segmentation and visualization... ..."

### Table 4. Model-based reductions of the complete pathway (model statistics) states transitions construction model checking

"... In PAGE 25: ... Similarly, the removal of the de- complexation of FGFR:FRS2 would only be noticeable over a very small time scale: as the rate of FRS2 and FGFR complexation is extremely fast, following the decomplexation of FRS2 and FGFR one would see the (re)complexation of FGFR and FRS2 almost immediately. Table4 gives the model statistics both for the complete model and the model obtained after applying the reductions (1), (2) and (3), both in isolation and collectively. The results show that reduction (1) - removal of Sos - yields the greatest decrease in state space of the three.... In PAGE 25: ... In general, it is therefore advantageous to look into a number of different reduction approaches, although, as already stated, this does re- quire some understanding of the model under study. Table4 also presents the times required for model construction and model checking of a single property (property H of Section 6) using each of the different combinations of model reductions. It can be seen that the decreases in model size are also reflected in these timings.... ..."

### Table 1. Comparison of Integration Approaches Nevertheless, several ideas and concepts of these approaches could be of high value for model-based tool integration.

"... In PAGE 4: ... Summarizing (cf. Table1 ), although there are already few approaches targeting model-based tool integration from a meta-modeling point of view and providing some basic abstraction mechanisms each of them suffers from certain deficiencies with respect to the focus of model-... ..."

### Table 4 ARMD trial

2007

"... In PAGE 17: ...ared. For the observed, partially incomplete data, GEE is supplemented with WGEE. Further, a random-intercepts GLMM is considered, based on numerical integration. The GEE analyses are reported in Table4 and the random-effects models in Table 5. For GEE, a working exchangeable correlation matrix is considered.... In PAGE 19: ... The advantage of having separate treatment effects at each time is that particular attention can be given at the treatment effect assessment at the last planned measurement occasion, that is, after one year. From Table4 it is clear that the model-based and empirically corrected standard errors agree extremely well. This is due to the unstructured nature of the full time by treatment mean structure.... In PAGE 20: ... The results for the random-effects models are given in Table 5. We observe the usual relationship between the marginal parameters of Table4 and their random-effects counterparts. Note also that the random-intercepts variance is largest under LOCF, underscoring again that this method artificially increases the association between mea- surements on the same subject.... ..."

### Table 2. Optimal views based on model-based reconstruction.

2004

"... In PAGE 5: ... Based on an average reconstruction time of 30 sec- onds, this search takes about 45 hours. The results are presented in Table2 which shows the optimal views for K = {1,2,3,4,5} and the correspond- ing minimum average reconstruction errors (refer to Table 1 Figure 7. Reconstruction errors for all view con- figurations with 4 cameras (K = 4) ranked by magnitude of ensemble error.... In PAGE 5: ... Figure 7 shows the errors of all combinatorial view configurations for the case K = 4, ranked in ascending order of error. Each er- ror bar represents the subjects standard deviation for that configuration (the first error bar corresponds to the optimal configuration and is the subject standard deviation listed in Table2 ). Other plots for K = 1,2,3 and 5 are quite sim- ilar in nature, all showing a well-defined minimum with the subject variation (error-bars) being lowest for the best configuration (left most) and highest for the worst (right most).... In PAGE 5: ... Using the same search strategy, we now evaluate the visual hull constructions ob- tained from the given subset of silhouette images and com- pare them to the ground truth. Table 3 shows the optimal views for K = {2,3,4,5} and the corresponding error val- ues (same format as in Table2 except that the visual hull from a single silhouette (K = 1) has no finite volume and... In PAGE 6: ... There are a few dif- ferences but these are somewhat misleading. The best view configurations in Table2 are marked in Figure 8 with ar- rows. We note that our model-based optimal views have al- most the same errors as the best views chosen with visual hull method and are always in the first plateau or top quar- tile that includes the key profile view #10.... ..."

Cited by 7

### Table 9 Comparison of Actual and Model-Based GRPs

"... In PAGE 12: ... We caution the readers that the solution may not be optimal but provides a better allocation. One such allocation is reported in Table9 and depicted in Figure 5. The horizontal bar graph com- pares the improved and the actual allocation of resources (measured in total GRPs) across the dif- ferent themes.... In PAGE 12: ... Our model suggests increasing adver- tising expenditure on reconnect and reassurance ads while decreasing on the other three themes. The per- centage changes in allocation of GRPs are quite large as seen in Table9 . They range from a low of 50% to a high of 276% change.... ..."

### Table 2. Optimal views based on model-based reconstruction.

2004

"... In PAGE 7: ... Based on an average reconstruction time of 30 seconds, this search takes about 45 hours. The results are presented in Table2 which shows the optimal views for K = {1,2,3,4,5} and the correspond- ing minimum average reconstruction errors (refer to Table 1 for exact coordinates). The standard deviation of the indi- Figure 7.... In PAGE 7: ... Figure 7 shows the errors of all combinatorial view configurations for the case K = 4, ranked in ascending order of error. Each er- ror bar represents the subjects standard deviation for that configuration (the first error bar corresponds to the optimal configuration and is the subject standard deviation listed in Table2 ). Other plots for K = 1,2,3 and 5 are quite sim- ilar in nature, all showing a well-defined minimum with the subject variation (error-bars) being lowest for the best configuration (left most) and highest for the worst (right most).... In PAGE 7: ... Using the same search strategy, we now evaluate the visual hull construc- tions obtained from the given subset of silhouette im- ages and compare them to the ground truth. Table 3 shows the optimal views for K = {2,3,4,5} and the correspond- ing error values (same format as in Table2 except that the visual hull from a single silhouette (K = 1) has no fi- nite volume and is omitted). Note that a visual hull recon- struction (especially one from few images) is not a very... In PAGE 8: ... Interestingly, the first plateau corresponding to the top group is all the sub- sets which include the profile view #10 (one of the most salient). We can see marked similarities in the opti- mal views in Table2 and Table 3. For example, both methods indicate views #3 and #10 to be the most infor- mative.... In PAGE 8: ... For example, the two most salient views (#3 and #10) correspond very closely with the established (biomet- ric) standards of 3/4 view (INS photos) and profile view ( mugshot photos). We have not yet searched for K gt; 5 mainly due to the computational costs, but it appears that reconstructions do not improve significantly beyond 4-5 views (see the best errors listed in Table2 ). One can easily incorporate additional physical and operational constraints into our framework.... ..."

Cited by 7

### Table 4. Model-based reductions of the complete pathway (model statistics)

"... In PAGE 25: ... Similarly, the removal of the de- complexation of FGFR:FRS2 would only be noticeable over a very small time scale: as the rate of FRS2 and FGFR complexation is extremely fast, following the decomplexation of FRS2 and FGFR one would see the (re)complexation of FGFR and FRS2 almost immediately. Table4 gives the model statistics both for the complete model and the model obtained after applying the reductions (1), (2) and (3) both in isolation and collectively. The results show that reduction (1) - removal of Sos - yields the greatest decrease in state space of the three.... ..."