Sentence examples for problem distinguishing from inspiring English sources

Exact(6)

James Peters, told them that he recalls Detective Turetzky saying that he had a problem distinguishing Officer Schwarz from another officer with a similar haircut.

But before that order was in place, Dr. Damianos, a retired internist who also owns Long Island's largest vineyard, Pindar, on the North Fork, told Wine Spectator magazine that he thought customers would have no problem distinguishing between the two brands.

"Folk taxonomies" have long reflected the realization that the living world is organized into groups-within-groups that can be defined on the basis of characteristics that their members share; and nobody who has any familiarity with the living world has any problem distinguishing a bird from a bat or a flying fish.

Thus, for prostate cancer, there is a well-recognized problem distinguishing aggressive from low-risk cancer.

Novices had no problem distinguishing speed level across blocks of instructed speed, yet within the same block when the speed was instructed at random, their motions tended to blur the difference between speed levels.

This approach has some limitations, such as a limited number of enzymes requiring high purity, problem distinguishing between similar mono-/oligosaccharides, and a need to work with pure carbohydrates rather than with complex mixtures.

Similar(53)

The spectrum sensing problem distinguishes between two mutually independent Gaussian sequences y k), under hypothesis H0 and H1 respectively, as defined previously in Equation 1.

Hence, many energy forecasters deal with the problem of the treatment of public holidays (i.e. bank holidays or federal holidays) but the methods they use to approach this problem distinguish substantially.

The biggest went to the heart of Dr. Schwartz's contentions that the sensor had major problems distinguishing warheads from decoys.

The researchers found that all the poor readers, while normal in nearly every other measure of hearing, had problems distinguishing closely-spaced tones.

The area between 0.25 and 0.1 shows the largest variation in performance, when models can have problems distinguishing between activity classes.

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