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A substantial decrease in the rate of cervical cancer was seen after development of the Pap smear for screening. Between 1955 and 1992, the rate of death from cervical cancer decreased by 74%. Screening for and decreasing cervical cancer incidence and mortality is an increasing challenge in developing nations, where health care and



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during training It is found from these tables that the recognition scores on the training set, as expected, are higher than those on the test set The recognition score during training decreases with an increase in the value of l On the other hand, for the test data, the recognition score increases with l up to a certain value, beyond which it decreases This can be explained as follows During training, the recognition score increases when there is a decrease in l, due to a better abstraction capability although for the test data, as l decreases, the modeling of class structures improves because there is an increase in the number of cases, and therefore the recognition score increases up to a certain value of l Beyond that value, as mentioned in Section 371, the number of cases with poor generalization capability (ie.





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, similarity functions with very small bandwidth) increases As a result, the recognition score decreases due to overlearning As mentioned in Section 3722, the number of hidden nodes in the network decreases with an increase in l for all the example data (see Tables 33 and 34) Since class e of vowel data is most sparse, it needs a maximum number of cases (and hence a maximum number of hidden nodes) for its representation This is re ected in Table 33 Similar observations hold good for the medical data, where the class PH, being the sparsest, has the maximum number of hidden nodes From these tables it can be noted that for both the data sets, the stability of the architecture of their respective networks is achieved within a very few iterations.

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similar to that predicted after ooding at our site. Martius (1997) reported that woody decay rates in the Central Amazon oodplain are enhanced by the seasonal oscillation between wetting and drying. Decay rates during the terrestrial phase of the ooding cycle were greatest for wood that had been immersed for one to four weeks, as compared with wood that had not been submerged or wood that had been submerged for six months (Martius, 1997). Microbial and fungal activity in uence the rates of wood decomposition (Harmon et al., 1986), and such activity in turn is affected by temperature, moisture, and aeration (Marra and Edmonds, 1994; Rayner and Todd, 1979). In our study, microbial and fungal activity generally increased with ooding (Molles et al., 1998). Responses included increased abundance of soil bacteria, fungi, and cellulose decomposers, higher mycorrhizal inoculum potential and root lengths colonized by mycorrhizal fungi, and increased dehydrogenase activity, indicating biological activity in the soil. We also used respiration chambers to measure forest oor respiration during the second two experimental oods, as well as during one natural ood.

Because the hair is darker than the background, we can get more control over the Clone Stamp by changing its blending mode to Lighten. Make that change in the tool options. Now the tool will affect only pixels that are darker than the sampled area and will lighten them. (If this were light hair against a dark background, we d want to use the Darken blending mode.)

The effect of the size of a training set on the performance of the network is demonstrated in Table 35 only for the vowel data, as an example The different values of perc considered are 10, 20, 30, 40, 50, 60, and 70, with l 150:0, 2000, and 2500 (Note that the network achieves the best generalization capability.

Table 30-1

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