  After long arguments between positivism and falsificationism, the
verification of universal hypotheses was replaced with the confirmation of
uncertain major premises. Unfortunately, Hemple discovered the Raven Paradox
(RP). Then, Carnap used the logical probability increment as the confirmation
measure. So far, many confirmation measures have been proposed. Measure F among
them proposed by Kemeny and Oppenheim possesses symmetries and asymmetries
proposed by Elles and Fitelson, monotonicity proposed by Greco et al., and
normalizing property suggested by many researchers. Based on the semantic
information theory, a measure b* similar to F is derived from the medical test.
Like the likelihood ratio, b* and F can only indicate the quality of channels
or the testing means instead of the quality of probability predictions. And, it
is still not easy to use b*, F, or another measure to clarify the RP. For this
reason, measure c* similar to the correct rate is derived. The c* has the
simple form: (a-c)/max(a, c); it supports the Nicod Criterion and undermines
the Equivalence Condition, and hence, can be used to eliminate the RP. Some
examples are provided to show why it is difficult to use one of popular
confirmation measures to eliminate the RP. Measure F, b*, and c* indicate that
fewer counterexamples' existence is more essential than more positive examples'
existence, and hence, are compatible with Popper's falsification thought.
