### Table 7. Algorithm to check for EMB

1998

"... In PAGE 37: ...Table 7. Algorithm to check for EMB The algorithm, which is shown in Table7 , is an adaptation to our framework of the algorithm described in [13] (which could be applied to the functional semantic models of finite-state terms of G), which is in turn a variant of the algorithm proposed in [29] to solve the relational coarsest partition problem. Given a labeled transition system with state space S representing the union of the integrated semantic models of two finite-state terms of G to be checked for EMB, or the integrated semantic model of a finite-state term of G to be minimized with respect to EMB, the idea of the algorithm is to repeatedly refine the current partition until this is a strong EMB.... In PAGE 38: ...By following the proposal of [29], this algorithm can be implemented in O(m log n) time and O(m + n) space where n is the number of states and m is the number of transitions. It is worth noting that a variant of the algorithm in Table7 can be used to compute the coarsest ordinary lumping [37] of the Markovian semantics of a given term, hence allowing for the determination of performance measures by solving a smaller Markov chain which is equivalent to the original one. Definition 5.... ..."

Cited by 74

### Table 1. Base and Modified Design Deviations Base Design Modified Design

"... In PAGE 8: ... (1)) which, in the case of the base design, computes to 2.45 (see Table1 ). It is the formal goal of the DBDS to minimize this error and, thus, meet the functional ... In PAGE 9: ... This candidate proposes a modified design, which is automatically implemented and evaluated by the DBDS. The resulting pattern of deviations (see Table1 ) results in an error level less than 0.05, which is within the level of noise generated by the Monte-Carlo simulation of the assembly.... ..."

### Table 1. Scope designators in pointcut expressions

"... In PAGE 12: ... As an example, within application-specific instances of the vec- tor class, there may be subtle points of variability required for a specific vector instance. To characterize this behavior, Table1 illustrates the scoping rules for a pointcut description notation. The table is not a comprehensive list of all possible pointcut designators, but it captures the essential ones that will be explained with suitable examples.... In PAGE 13: ... 13 From the categorization of scope designators shown in Table1 , the example from Listing 3 can be re-visited to observe the scoping rules for classes A and B in the ap- plication program. At the bottom of Listing 3, two pointcut specifications are shown that capture the logging concern for specific vector instances depending on the scoping rule applied to the base class template.... In PAGE 15: ... Full template specialization of the original vector template However, additional scoping constraints may state that such type morphing is only applicable to certain instances of type T1 in the application program with other in- stances remaining unaffected. The scoping expressions presented in Table1 in con-... In PAGE 34: ... Furthermore, a contribution of the paper demon- strated the ability to modularize crosscutting concerns in scientific libraries. The research described in this paper is a modest initial effort that is at an early stage in terms of the construction of a concrete aspect language to cover the different situations of template instantiation (as in Table1 ). Future directions will involve ex- tending the focus to other scientific libraries that are implemented in C++ (e.... ..."

### Table 2. Comparison of implementation changes for proposed methodologies

"... In PAGE 3: ... Traditional processor memory archi- tecture DCache ICache Cache L2 Data bus Data address bus Instruction bus address bus Instruction Core Processor Main Memory Stack (512x32) Figure 3. Stack based processor memory ar- chitecture Table2 shows the comparison of the design changes that would be needed for each of the proposed implementation... ..."

### Table 2: Freely available computational tools for quantification of differential expression. Computational tools for quantification of differential expression that are freely available are summarized in this table. For detailed information on the functions that are available on the Bioconductor homepage we refer to the vignettes of the respective packages. Otherwise detailed information is either given on the cited homepage or within the respective article

2006

"... In PAGE 7: ... Many authors offer fi-eely available computational tools. Table2 provides an overview of these tools. Lonnstedt and Speed [43] introduce a parametric empirical Bayes approach.... In PAGE 8: ... Storey etal [55] propose a statistical framework specifically designed for time course analysis. This spUne-based approach has been implemented in the open-source software package EDGE ( Table2 ). To assign significance to each gene or group of genes they use a (-statistic and F-statistic related approach.... ..."

### Table 2: The signal states of the kill bus in the token- based selective replay.

2004

"... In PAGE 9: ... For this purpose, a kill signal for each token consists of two wires that express four states. Table2 shows these signal states of the kill bus and the operations to perform. Performance evaluation of token-based selective replay, compared with other replay schemes will be presented in Section 5.... ..."

Cited by 19

### Table 2: The signal states of the kill bus in the token- based selective replay.

2004

"... In PAGE 9: ... For this purpose, a kill signal for each token consists of two wires that express four states. Table2 shows these signal states of the kill bus and the operations to perform. Performance evaluation of token-based selective replay, compared with other replay schemes will be presented in Section 5.... ..."

Cited by 19

### Table 3.Energy consumption per frame between bus-based and P2P implementation

### Table 7-9. Final Sampling Design. (2 pages)

1996

"... In PAGE 48: ...1.1 Screening Method Alternatives Table7 -1 identifies all of the screening technologies that were considered to resolve each decision statement and the optional methods of implementing each technology. The table also summarizes the limitations associated with each screening technology and/or method of implementation and provides an estimated cost for implementation.... In PAGE 48: ... The table also summarizes the limitations associated with each screening technology and/or method of implementation and provides an estimated cost for implementation. Table7 -1. Summary of Screening Alternatives.... In PAGE 48: ...1.2 Sampling Method Alternatives Table7 -2 identifies the various types of media that need to be sampled to resolve each decision statement and alternative methods for collecting these samples. The table presents alternative... In PAGE 49: ... An estimated cost for the implementation of each sampling design has also been provided for comparison purposes. Table7 -2. Summary of Sampling Method Alternatives.... In PAGE 49: ...1.3 Implementation Design Table7 -3 presents the selected screening technology(s) and sampling method(s) for resolving each decision statement and a summary of the proposed implementation design. The table also provides the rationale for selected methods and design.... In PAGE 49: ... The table also provides the rationale for selected methods and design. Table7 -3. Selected Judgmental Design.... In PAGE 50: ...2.1 Data Collection Design Alternatives Table7 -4 identifies the statistical design alternatives (e.g.... In PAGE 50: ...able 7-4 identifies the statistical design alternatives (e.g., simple random, stratified random, and systematic) that were evaluated for each decision statement, as well as the selected design and the rationale for the selection. Table7 -4. Selected Statistical Design.... In PAGE 50: ...2.2 Mathematical Expressions for Solving Design Problems Table7 -5 identifies the statistical hypothesis test (e.g.... In PAGE 51: ...Rev. 0 7-4 Table7 -5. Statistical Methods for Testing the Null Hypothesis.... In PAGE 52: ...2.3 Select the Optimal Sample Size that Satisfies the Data Quality Objectives Table7 -6 presents the total number of samples required to be collected for each decision statement with varying error tolerances and varying widths of the gray region. The total number of samples was calculated using the statistical method identified in Table 7-4.... In PAGE 52: ....2.3 Select the Optimal Sample Size that Satisfies the Data Quality Objectives Table 7-6 presents the total number of samples required to be collected for each decision statement with varying error tolerances and varying widths of the gray region. The total number of samples was calculated using the statistical method identified in Table7 -4. As would be expected, the higher the error tolerances and wider the gray region, the smaller the number of samples that are required.... In PAGE 52: ...7 [EPA 1989]). As shown in Table7 -4, the fill material in 105-F FSB is considered analogous to waste site overburden, thus, the 100 Area SAP (DOE-RL 1998a) sampling strategy will be used. Table 7-6.... In PAGE 52: ...-Test (formula 6.7 [EPA 1989]). As shown in Table 7-4, the fill material in 105-F FSB is considered analogous to waste site overburden, thus, the 100 Area SAP (DOE-RL 1998a) sampling strategy will be used. Table7 -6. Sample Size Based on Varying Error Tolerances and LBGR.... In PAGE 53: ...2.4 Sampling Cost For varying error tolerances, and varying widths of the gray region, Table7 -7 presents the total cost for sampling and analyzing the number of samples identified in Table 7-6. As would be expected, the higher the error tolerances, the wider the gray region, the lower the sampling and analysis costs.... In PAGE 53: ...2.4 Sampling Cost For varying error tolerances, and varying widths of the gray region, Table 7-7 presents the total cost for sampling and analyzing the number of samples identified in Table7 -6. As would be expected, the higher the error tolerances, the wider the gray region, the lower the sampling and analysis costs.... In PAGE 53: ... Consult the appendices in the Remedial Design Report/Remedial Action Workplan for the 100 Area (DOE-RL 1998b) for the results of the trade-off analysis. Table7 -7. Sampling Cost Based on Varying Error Tolerances and LBGR.... In PAGE 53: ... It is important to consider trade-offs so contingency plans can be developed and the added value of selecting one set of considerations over another can be quantified. Table7 -8 identifies the sampling design that provides a balance between the known operational limitations and the ability to meet the DQOs. Once the sample design has been defined, the project may conduct a trade-off analysis to determine if the reused potential... In PAGE 54: ...Rev. 0 7-7 Table7 -8. Most Resource-Effective Data Collection Design.... In PAGE 54: ... If required, one or more outputs to DQO Steps 1 through 6 were modified to tailor the design to most efficiently meet all of the DQO constraints. For each decision statement, Table7 -9 presents a summary of the final statistical sampling design, the total number of samples to be collected. Sampling will be performed as described in Table 7-8.... In PAGE 54: ... Sampling will be performed as described in Table 7-8. Table7 -9. Final Sampling Design.... ..."

Cited by 2