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Table 4. Exception cases indexed by the symbolic rules in Table 3

in Integrating Hybrid Rule-Based with Case-Based Reasoning

by Jim Prentzas, Ioannis Hatzilygeroudis 2002

"... In PAGE 9: ...As an example, consider the three symbolic rules (R2, R3, R4) presented in Table 3. Table4 presents some of their exception cases. The symbolic rule for which each of these example cases is an exception, is shown in the apos;disease-type apos; column of the table in parenthesis.... In PAGE 9: ... Merging these three symbolic rules produces the neurule presented in Table 5. The cases in Table4 are now indexed as exceptions to this neurule. This example demonstrates how the average number of exception cases indexed by a neurule is increased if it is produced from a merger set of symbolic rules indexing exception cases.... In PAGE 10: ... Firing of the neurule is suspended and the exception cases matching the explanation rule are considered in the case-based reasoning process. From the exception cases shown in Table4 , only the fourth one matches the explanation rule. Table 7.... In PAGE 11: ...e., the fourth case in Table4 ) will be considered by case-based reasoning. Therefore, both types of inference mechanisms produce the same results.... ..."

Cited by 2

Table 2: Eleven exceptional cases of vertex-minimal triangulations.

in unknown title

by unknown authors

Cited by 1

Table 16 Stability results for infant sleep cases type min

in Modeling Instability In The Control System For Human Respiration: Applications To Infant Non-REM Sleep

by J. J. Batzel, H. T. Tran 2000

"... In PAGE 26: ... A fast transition time to the sleep state and increased maximal shift SO (nearly equal to the awake ventilatory drive [59]) and an increase in arousal threshold produces this case. See Table16 . The... In PAGE 29: ... When arousal threshold is increased by 25 % apneic periods are in the range of 15 seconds and O2 saturation decreases to levels of signi cant hypoxia as de ned in [116]. See Table16 for comparisons. As seen below, the number of apneas per minute can be reduced by assuming a longer aroused period.... In PAGE 30: ...ig. 26. this shift in Sw is completed early in this transition phase. See Table16 . A variety of e ects can be produced by various combinations of Sw transition time, SO magnitude, arousal and minimum threshold levels and control gain levels.... ..."

Cited by 1

Table 3 Properties of Awow~~ structures used to waluate the method .

in unknown title

by unknown authors 1994

Cited by 24

Table 2 Long run average financial cost for piped water/1 Estimated average cost of water, US$ / cubic meter

in Pricing, Subsidies and the Poor: Demand for Improved . . .

by Ian Walker, Fidel Ordoñez, Pedro Serrano, J. Halpern

"... In PAGE 8: ... This tariff is set to generate a real rate of return of 12%. Table2 summarizes the resulting estimates. This allows us to establish whether a given household is receiving a subsidy.... ..."

Table 1. Resuming Execution after Exception Handling Case nodestate (n, i) = Active nodestate (n, i) = Scheduled

in On Capturing Exceptions in Workflow Process Models

by Shazia W. Sadiq, Maria E. Orlowska 2000

Cited by 7

Table 1. Resuming Execution after Exception Handling Case nodestate (n, i) = Active nodestate (n, i) = Scheduled

in On Capturing Exceptions in Workflow Process Models

by Shazia W. Sadiq, Maria E. Orlowska

Cited by 1

Table I Moreover for m even, Dm(x, t) is irreducible except in the following cases:

in unknown title

by unknown authors 2008

Table 3. Extending annotations of a music collection by means of CB similarity. We observe that the propagation grows with a smaller number of similars and a higher per- centage of annotated songs, except for the case of 40% and 50%.

in ANNOTATING MUSIC COLLECTIONS: HOW CONTENT-BASED SIMILARITY HELPS TO PROPAGATE LABELS

by unknown authors

"... In PAGE 2: ... Finally, we propose another experiment that is to auto- matically annotate songs in a music collection by means of the propagation process. The results are presented in Table3 . It is clear that the percentage of songs automati- cally annotated by CB similarity increases when the num- ber of already annotated songs grows.... ..."

(Table 2). The main point to make here is that temptation are indices usually fairly large or fairly low except the cases where the subject and object levels are close. This is the place where calculated risk taking should be allowed.

in Fuzzy MLS: An Experiment on Quantified Risk–Adaptive Access Control

by Pankaj Rohatgi, Claudia Keser 2007

Results 1 - 10 of 59,930

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Table 4. Exception cases indexed by the symbolic rules in Table 3

Table 2: Eleven exceptional cases of vertex-minimal triangulations.

Table 16 Stability results for infant sleep cases type min

Table 3 Properties of Awow~~ structures used to waluate the method .

Table 2 Long run average financial cost for piped water/1 Estimated average cost of water, US$ / cubic meter

Table 1. Resuming Execution after Exception Handling Case nodestate (n, i) = Active nodestate (n, i) = Scheduled

Table 1. Resuming Execution after Exception Handling Case nodestate (n, i) = Active nodestate (n, i) = Scheduled

Table I Moreover for m even, Dm(x, t) is irreducible except in the following cases:

Table 3. Extending annotations of a music collection by means of CB similarity. We observe that the propagation grows with a smaller number of similars and a higher per- centage of annotated songs, except for the case of 40% and 50%.

(Table 2). The main point to make here is that temptation are indices usually fairly large or fairly low except the cases where the subject and object levels are close. This is the place where calculated risk taking should be allowed.