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Table 4 - Datrix metrics domain mapping to ISO 9126 maintainability sub-characteristics
"... In PAGE 6: ... In systems made up of independent components with well defined roles, linked through strict interfaces, a designer knows where to start to solve a problem since determining which component is responsible for an undesired behavior is unambiguous. Table4 shows which Datrix metrics domains are used to assess each of the four ISO-9126 maintainability sub-characteristics. Table 4 - Datrix metrics domain mapping to ISO 9126 maintainability sub-characteristics ... ..."
Table 1: Few Important Member Functions of CSP Simulation class CSPnodelist Method / Variable name Maintained by
in Implementing Multi-MoC Extensions for SystemC: Adding CSP & FSM Kernels for Heterogeneous Modeling
"... In PAGE 14: ... Table1 presents some important member functions used in the initialization and simulation of a CSP model. We discuss some of these function in detail here.... In PAGE 14: ...imulation of the CSP model starts by calling the sc csp start(...) function. Table1 shows a list of some important functions and variables and whether the CSP kernel or the QuickThread package manages them [6, 9]. The variable m cor pkg is a pointer to the file static instance of the coroutine package.... ..."
Table VII shows the same information as Table VI but for = 4 features processed per second and 0 = 0:2 features per second. Figures 5 and 6 plot the work completion probability versus processing start time for the examples in Table VI. Figures 7 and 8 do the same for the examples in Table VII. The above tables and figures show that the system can tolerate later processing start times for batch processing when the source process spends more time in the state with the higher feature arrival rate. This follows our intuition since in order to maintain the average utilization with fixed 0, 1 must be higher when the system spends
Table 1: Example 1. IWR problem for \numa quot;. (a) De nition of the problem. (b) RGTRUST1 and TRENNS performances. Viceversa, Example 2 (see Tab. 2 and Fig. 1b) clari es a slightly di erent feature of RGTRUST1. In this case, in fact, RGTRUST1 approaches a minimum(error value 20:0), with a strong improving factor in comparison with TRENNS, con rming its e ciency in local optimisation. Searching for a better solution, RGTRUST1 jumps out of the neighbourhood of the KT point, maintaining an error value greater than that achieved by TRENNS. After 350 epochs, it starts approaching again the initial solution. Such a behaviour suggests that the latter solution is probably the global minimum, even if no theoretical proof has been found.
in A New Heuristic Global Algorithm for Automatic Speech Recognition Using Recurrent Neural Networks
Table 5.3 Algorithm Usage of Various Detection Tests
1991
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Table 2: External libraries used to index data
2006
"... In PAGE 7: ... The first discussion on the common searching API over DBUS was started by the maintainer of the Strigi project1, but maybe now is the time to start discussion on the common data source plugin API. The Table2 presents external libraries or programs that are used to index the data... ..."
Table 4: Summary of Maintainability Results
2006
"... In PAGE 7: ...able 3: Raw Maintainability Results............................................................................... 30 Table4 : Summary of Maintainability Results.... ..."
Table 3: Maintaining bounded inconsistency.
1999
"... In PAGE 12: ... As a consequence, the degree may be bounded either by limiting the number of weak writes pending commitment or by controlling the h function. In Table3 , we outline ways of maintaining d-consistency for di erent ways of de ning d. 4 A Consistency Restoration Schema After the execution of a number of weak and strict transactions, all core copies of a data item have the same value, while its quasi copies may have as many di erent values as the number of clusters.... ..."
Cited by 33
Table 1: Measurements of Maintainability Characteristic
2007
"... In PAGE 10: ... From the previously described quality metrics, we have so far automated the calculation of those related to maintainability. Table1 shows some results of the calculated metrics for different versions of the SIP test suite (we designed the quality metrics to yield a value between 0, i.... ..."
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Table 1 describes the information maintained by
2000
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