### Table 6. Deleting multi-element and dominating values

"... In PAGE 9: ... So we can eliminate all dominating values from the domain without changing the characteristics of the problem. Here, we just show for vacq the details of deleting multi-elements and dominating values in Table6 , and the resulting domain of the four variables is shown in Table 7. Table 6.... ..."

### Table 12: Compressive Strength of Wasteforms Prepared With Multi-element Mix Water After 60 Days of Curing

"... In PAGE 10: ...able 11: pH of Leachwater During First 456 Hours of Leach Testing ......................................52 Table12 : Compressive Strength of Wasteforms Prepared With Multi-element Mix Water After 60 Days of Curing.... In PAGE 42: ...3.2 Compressive Strength The results of the compressive strength tests are shown in Table12 (page 53). All wasteforms were above the U.... ..."

### Table 7: Initial Mass of Waste Elements in Wasteforms Produced With Multi-element Mix Water

"... In PAGE 10: ...able 6: Concentration of Elements in Mix Waters ...................................................................47 Table7 : Initial Mass of Waste Elements in Wasteforms Produced With Multi-element Mix Water.... In PAGE 26: ... mi = Ci(OPC) x mOPC + Ci(pozzolan) x mpozzolan + Ci(mix water) x mmix water. (1) Where: mi = mass of element i in wasteform Ci(OPC) = concentration of element i in the OPC Ci(pozzolan) = concentration of element i in the pozzolan used Ci(mix water) = concentration of element i in the mix water mOPC = mass of OPC used mpozzolan = mass of pozzolan used mmix water = mass of mix water used The results of these calculations are shown in Table7 (page 48) and Table 8 (page49). 2.... ..."

### Tables Table 1: Characteristics of Wasteforms Produced With Multi-element Mix Water

### Table 4. Experimental results on optimal test access architecture design under power constraints: (a) S 1 (b) S 2 .

"... In PAGE 5: ... G i can be obtained from power models for core i. Experimental results for power-constrained test access archi- tecture design for S 1 and S 2 are shown in Table4 . For our ex- periments, we approximated G i by the number of gates in core i.... In PAGE 5: ... On the other hand, for higher values of W, the testing time is affected substantially. For example, in Table4 (a), for W 24 and power budget of 300 units, the testing time does not decrease with an increase in W due to power constraints. In some cases, the ILP problem may even be infeasible for higher test widths, e.... In PAGE 5: ...g. in Table4 (b) with W =48 and power budget of 300 units for S 2 . Comparing with Table 2, we note that the width distribution is also significantly different due to power constraints.... In PAGE 5: ... This is achieved using a width distribution of (10,10) and test bus assignment (2,2,2,2,2,2,2,2,2,1). However, as seen from Table4 . for test width W =24, the test bus assignment has to be changed to meet power constraints, and the minimum testing time increases to 471900 cycles.... ..."

### Table 4. Experimental results on optimal test access architecture design under power constraints: (a) S1 (b) S2.

2000

"... In PAGE 5: ... Gi can be obtained from power models for core i. Experimental results for power-constrained test access archi- tecture design for S1 and S2 are shown in Table4 . For our ex- periments, we approximated Gi by the number of gates in core i.... In PAGE 5: ... On the other hand, for higher values of W, the testing time is affected substantially. For example, in Table4 (a), for W 24 and power budget of 300 units, the testing time does not decrease with an increase in W due to power constraints. In some cases, the ILP problem may even be infeasible for higher test widths, e.... In PAGE 5: ...g. in Table4 (b) with W = 48 and power budget of 300 units for S2. Comparing with Table 2, we note that the width distribution is also significantly different due to power constraints.... In PAGE 5: ... This is achieved using a width distribution of (10,10) and test bus assignment (2,2,2,2,2,2,2,2,2,1). However, as seen from Table4 . for test width W = 24, the test bus assignment has to be changed to meet power constraints, and the minimum testing time increases to 471900 cycles.... ..."

Cited by 44

### Table 7 Optimization variables and constraints

2003

"... In PAGE 10: ... As in the case of the electrostatic generator design, with the basic topology decided, a formal optimization can be performed in order to choose parameter values. The parameters over which the design is optimized, and the design constraints are shown in Table7 . Designs with two common piezoelectric materials have been considered: lead zirconate titanate (PZT), which is a ceramic, and poly- vinylidene fluoride (PVDF), which is a polymer.... In PAGE 11: ... Depending on the application, additional individual constraints could be put on the total length or width of the device, rather than just on the total area. Referring to Table7 , the best obtainable output power is about 250 mW. This matches the power predicted by the general model discussed in Section 4 very well, which results in an output power of 252 mW for the same input, damping conditions, and mass.... ..."

Cited by 29

### Table 1.1. Transition Matrix for Light Bulb State Machine

### Table 6.2. Transition Matrix for Light Bulb

### Table 4: Performance of optimal design for design example.

2001

"... In PAGE 26: ... Speci cation/Constraint Value Device length 0:8 m Device width 2 m Area 10000 m2 Common-mode input voltage xed at (VDD + VSS)=2 Output voltage range [0:1(VDD ? VSS); 0:9(VDD ? VSS)] Quiescent power 5mW Open-loop gain 80dB Unity-gain bandwidth Maximize Phase margin 60 Slew rate 10V= s Common-mode rejection ratio 60dB Input-referred spot noise, 1kHz 300nV=pHz Table 2: Speci cations and constraints for design example. The performance achieved by this design, as predicted by the program, is summarized in Table4 . The design achieves an 86MHz unity-gain bandwidth.... ..."

Cited by 29