### Table 6: Impact of Movie Broadcasts on Piracy (Fixed Effects) for Broadcast Channels

1977

"... In PAGE 10: ...10 Twenty Eighth International Conference on Information Systems, Montreal 2007 Our results in Table6 show a significant increase in piracy immediately after movies are broadcast on over-the-air channels. Daily downloads, number of lechers, and number of seeds increase over the next 3 weeks after the broadcast.... ..."

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### Table 1. Expectation and information sets (a system without feedback).

1997

"... In PAGE 12: ... Just three cases will be considered (shown in Figure 1), (a) =1;; =0;; (b) = 1 2 ;; = 1 2 ;; and (c) =0;; =1 Two error structures are interesting: case (i) where e t NID(0;; 0:1 2 )isa less volatile case, and thus leading indicator dominates x t ;; case (ii) where e t NID(0;; 1 2 )hasamorevolatile error structure, so that the random component (error term) dominates x t compared with that part generated by the leading indicator. Table1 and Appendix A show E[x t jx t;1 ;;y t;1 ]andE[x t jx t;1 ]ineach model. Table 1 presents the nine distinct predictive models resulting under the three generating models, when the information set is full or partial, and variance is 0:1 2 or 1.... In PAGE 12: ... Table 1 and Appendix A show E[x t jx t;1 ;;y t;1 ]andE[x t jx t;1 ]ineach model. Table1 presents the nine distinct predictive models resulting under the three generating models, when the information set is full or partial, and variance is 0:1 2 or 1. The full information set allows the predictive model to match the generating model.... In PAGE 14: ... The rst generating model in =1 and =0 is actually the same, two independent random walk equations;; but in the other twomodels,y t and x t feed into each other symmetrically. Unsurprisingly, the predictivemodels for the random walks are identical to those of Table1 . The most interesting di erences occur for =0 and =1, simplest generating model;; while the full information result is identical (as for the other two generating models), the partial-information predictive models both collapsed to x t;2 .... ..."

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### Table 2. Time distance and MSFE (a system without feedback).

1997

"... In PAGE 12: ... With partial information where y t is unavail- able for the forecast, the predictive model is quite sensitivetovariance;; with greater variance, more past values of x t appear in the predictive model, and coe cients are otherwise changed. Table2 presents di erent measures of t for predictive models result- ing across di erent generating models, as variance and information sets are changed. Consider rst MSFE.... In PAGE 14: ... This result obtains because now x t;2 is an excellent proxy for y t;1 . Table 3 is the counterpart to Table2 , presenting measures of t. The results for MSFE are as in Table 2, except that the relative magnitudes are smaller, especially in the cases of higher variance and limited information.... In PAGE 14: ... Table 3 is the counterpart to Table 2, presenting measures of t. The results for MSFE are as in Table2 , except that the relative magnitudes are smaller, especially in the cases of higher variance and limited information. Overall, the guidance provided by S t in Table 3 is much the same as that in Table 2, having the same relationships with information sets and leading indicator dominance.... In PAGE 14: ... The results for MSFE are as in Table 2, except that the relative magnitudes are smaller, especially in the cases of higher variance and limited information. Overall, the guidance provided by S t in Table 3 is much the same as that in Table2 , having the same relationships with information sets and leading indicator dominance. S sign t in general directs us to the predictivemodels corresponding to the simplest generating models with feedback, and away from the random walk models.... ..."

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### Table 5. Full state and output feedback control laws with sensor numbers.

1998

"... In PAGE 20: ... The ideal case is to eliminate the acoustic sensors entirely and use the model with coupling along with structural data to reconstruct the acoustic state. For the simulations presented here, three sensor con gurations were considered as sum- marized in Table5 . In all cases, the number of sensors measuring the potential was taken to be N = 0 in (2.... In PAGE 22: ... In comparing the rms values and time plots of the three compensators, it is noted that the performance of Compensator I with measurements of pressure, displacement and velocity is only 1-2 dB better than that of Compensators II and III. Recall from Table5 that Compensator III employs only 5 velocity sensors for the actual state reconstruction. The pre- computed gains and coupled model provide the remaining information required for accurate state estimation and control computation.... In PAGE 25: ... Hence while signi cant attenuation is achieved throughout most of the cavity, optimization issues concerning patch number and orientation should be investigated to attain global attenuation. Similar results obtained with Compensators I and III described in Table5 are plotted in Figure 9. The small patch having radius R=12 was employed as an actuator and rms sound pressure levels along axis 2 are reported in the gure.... In PAGE 27: ... The example we consider in this section reinforces the tenet held by many acousticians that this strategy is not e ective in general and should be used only for certain exogenous frequencies (see, for example, [13, 20]). It also illustrates the bene ts of utilizing a compensator for the coupled system which employs only structural sensors (see Compensator III of Table5 ) rather than a purely structural controller. For the structural acoustic system in this work, a purely structural controller would be designed for the discretized plate model quot; KP 0 0 MP # quot; _ #(t) #(t) # = quot; 0 KP ?KP ?CP # quot; #(t) _ #(t) # + quot; 0^ B # u(t) + quot; 0 ^ g(t) # + ^ D (t) where again, #(t) contains the generalized Fourier coe cients for displacement and MP ; KP and CP are the mass, sti ness and damping matrices for the plate (see Section 2).... ..."

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### Table 1-1. Output Data Comparison based on the raw Paramics1.5 Total Demand Paramics1.5 VDS* Error (%)

1999

"... In PAGE 31: ... Outputs aggregated in this step for further comparison include 1) total generation (total vehicles released in 2 hours), 2) total attractions (total number of vehicles completing the short journey in 2 hours), 3) lane-by-lane outflow (the number of vehicles collected from each lane in 2 hours), and 4) % lane-by-lane usage. Results in Table1 -1 indicate a shortage in the number of vehicles being released to the section, the number of vehicles traversing the section, and a severe lane usage problem. Therefore, parameter... In PAGE 32: ... The final combinations in the Vehicle file are shown in Table 1-2. Table1 -2 The Calibrated Parameters in the file Vehicle of Paramics1.5 Vehicle Composition Type-1 car Proportion 71 Type-2 car HOV Proportion 4 Type-3 car HOV Proportion 3 Type-4 car Proportion 2 Type-12 lgv Proportion 4.... In PAGE 33: ... The selected parameters in the file Driver are shown in Table 1-3. Table1 -3 Aggressiveness and Awareness Parameters in the file Driver of Paramics1.5 aggressiveness multiple 3 slides 1 4 11 21 28 21 1141(normaldistribution) awareness multiple 1 slides 1 4 11 21 28 21 1141(normaldistribution) Another important insight gained from the above experimentation is that the usage of lane-1 (the outside lane) and lane-2 is affected by the shaping of the destination zone.... In PAGE 34: ... Table1 -4. Improved Results Total Demand Paramics1.... ..."

### Table 1. Results without cooperation

2005

"... In PAGE 12: ...66 GHz Pentium 4), and therefore the execution time is biased by the parallelism inherent in the simulation, which loads the single processor with a considerable computational overhead. In Table1 , we show the best results obtained in terms of RMSD and energy without cooperation, while in Table 2 cooperation was active. The energy considered here is the one presented in Section 4; the contributions of cooperative computational fields are not considered.... In PAGE 13: ...Table1 , we can see that, without cooperation, the simulation is quite stable: most of the runs produce solutions with energy varying in a very small range of values. On the contrary, the RMSD is quite high.... In PAGE 13: ... Anyway, when we introduce also the secondary structure information, the situation changes, and the RMSD is improved in most of the cases (cf. Table1 and 2). This is quite remarkable, as the information relative to secondary structure is still local.... In PAGE 14: ... Therefore, the sim- ulation gets stuck very easily in bad local minima, and reaches good solutions just by chance. The results shown in Table1 , instead, are obtained activating the orchestra director agent just a couple of times for each value of the temperature. This suffices to obtain much better energy minima.... ..."

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### Table 1. Results without cooperation

2005

"... In PAGE 12: ...66 GHz Pentium 4), and therefore the execution time is biased by the parallelism inherent in the simulation, which loads the single processor with a considerable computational overhead. In Table1 , we show the best results obtained in terms of RMSD and energy without cooperation, while in Table 2 cooperation was active. The energy considered here is the one presented in Section 4; the contributions of cooperative computational fields are not considered.... In PAGE 13: ...Table1 , we can see that, without cooperation, the simulation is quite stable: most of the runs produce solutions with energy varying in a very small range of values. On the contrary, the RMSD is quite high.... In PAGE 13: ... Anyway, when we introduce also the secondary structure information, the situation changes, and the RMSD is improved in most of the cases (cf. Table1 and 2). This is quite remarkable, as the information relative to secondary structure is still local.... In PAGE 14: ... Therefore, the sim- ulation gets stuck very easily in bad local minima, and reaches good solutions just by chance. The results shown in Table1 , instead, are obtained activating the orchestra director agent just a couple of times for each value of the temperature. This suffices to obtain much better energy minima.... ..."

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### Table 1: Wireless links require special treatment, depending on the number of users, and the amount of channel state information (CSI) that is available.

"... In PAGE 2: ... A detailed survey of information theory for fading channels is given in [2]. For our purposes it is convenient to subdivide the multiple-antenna problem area as shown in Table1 , with a limited... ..."

### Table 5.1: Static user interests: e ect of feedback

1994

"... In PAGE 49: ....1.2 Questionnaires In addition to the numerical data collected above, a questionnaire was also distributed to the users to get feedback on the subjective aspects of the system. A copy of the questionnaire is shown in Table5 -7. Some of the questions were directly pertinent to the system and dealt with ease of use and user-friendliness.... ..."

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