Sentence examples for using a single random from inspiring English sources

For these preliminary analyses, we carried out 100 parsimony bootstrap replicates using a single random sequence addition replicate, limiting the search to 50 min per dataset and storing a maximum of 1000 trees per search.

In case the coefficient of Eq. (16) monitoring the fatigue crack initiation and growth is modeled using a single random variable, the time to crack initiation is the same for the four sites where cracks initiate (at the holes of the structure shown on Fig. 6).

We also design a barely random online algorithm for the D-benevolent case and the case of unit intervals, which uses a single random bit, and has a competitive ratio of 3.22745.

Thus, we use a single random variable to refer to them.

Second but more importantly, we used a single random blood glucose measurement on admission to define hyperglycemia.

We used a single random measurement of urine albumin to assess albuminuria rather than three measurements; again, this approach has been used previously by many other investigators (12, 13), and recent data suggest that single urinary albumin measurements are accurate in predicting nephropathy and appropriate for epidemiological studies (13).

Mass transfer across a free interface was characterized by using a single eddy with random surface renewal.

Additionally, the classification for diabetes, prediabetes, and normal glycemia was determined using a single fasting or random glucose measurement among those who did not use insulin or oral diabetes medications and did not report a history of diabetes.

A further alternative using a single set of random effects was proposed by Stern and Cressie (1999), but this and other extensions have a single spatial autocorrelation parameter (for the BYM model it is the ratio of the two random effects variances) that controls the level of spatial smoothing globally across the entire region.

The selection of cases from the sampling frame (2000 census) was performed using a single-stage random procedure.

The base clustering generates diverse clustering solutions through: 1) generating subspace datasets using gene resampling [ 1, 2, 4]; 2) using a single clustering algorithm with random parameter initializations such as selecting a random number of clusters [ 3, 4]; 3) using different clustering algorithms for each base clustering [ 5].