Sentence examples for evaluation of mixed from inspiring English sources
Instead of a straight forward comparison of strictly separated processes, an evaluation of mixed processes derived from an observation of practical actions was evaluated.
With the findings obtained, seven annoyance models so far proposed for the evaluation of mixed source noise were examined.
The results demonstrate that the localised experimental numerical technique has potential for the evaluation of mixed mode strain energy release rates using localised test data.
The first is to validate the usefulness of the simulated environment method for the assessment of community responses, and the second is to validate the annoyance models so far proposed for the evaluation of mixed source noise.
Recent studies show also how the evaluation of mixed mode interface delamination phenomena, classical strength hypotheses along with fracture mechanics approaches and thermal fatigue estimation of solder joints can simultaneously be taken into account.
Both liquid turnover and pH must be taken into consideration for in vitro evaluation of mixed and concentrate diets for ruminants and this system provides a simple and inexpensive method for doing this.
A US review of interventions designed to address area characteristics (Anderson et al., 2003) searched for evaluations of mixed income housing developments in areas of high poverty, but found none of sufficient quality for inclusion.
Chimerism of live offspring was confirmed by evaluation of their mixed coat color.
Bukola et al. [6] experimentally found out the performance evaluation of a mixed-mode solar dryer for food preservation.
We report on the development and performance evaluation of the mixed-signal Application Specific Integrated Circuit ASICC) developed for the signal processing of onboard X-ray CCD cameras and various types of X-ray imaging sensors in astrophysics.
In summary, the M.I.N.I. module demonstrated good concurrent validity with psychiatrists' evaluation of DSM-5 mixed features in manic patients, accurately detecting mixed features with limited risk of over-diagnosis.
