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However, these measurements require multiple urine collections to reliably estimate intake; therefore, they may be impractical to collect for large study samples.
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Comprehensive quality measurement requires multiple perspectives, including those of children and families [ 2– 4].
Although phthalate bio-markers in urine are available to accurately measure a person's exposure at a single point in time, determining exposure over time intervals of weeks or months will require multiple measurements of phthalate metabolites.
Although the urinary concentrations of phthalate metabolites can be used to accurately measure the exposure of a person at a single point in time, because of the short elimination half-life (t1/2) of phthalates (i.e., a few hours) (Koch and Calafat 2009), determining exposure over weeks or months may require multiple measurements.
In fact, many industrial processes are complex and contain multiple components, which require multiple measurement techniques to individually quantify them.
Airborne exposures from cleaning products are challenging to quantity because they are complex mixtures of ingredients having a range of volatilities and other physicochemical properties and thus require multiple measurement techniques [ 21, 22].
The data from the study by LaBerge et al. [ 40] confirmed that NC measurements have very good inter- and intra-rater reliability and, consequently, they do not require multiple repeated measurements for precision and reliability.
However, both consensus or flooding-based solutions are very costly in terms of bandwidth requirements as they require multiple iterative inter-node communication between two consecutive sensor measurements.
This feature differs from existing sensors, which require multiple fingerstick BG measurements over the life of the sensor for calibration.
Currently, detection of airway occlusion due to OSAHS is achieved by indirect measurements, often requiring multiple sensor types, such as a flow transducer combined with chest and abdomen plethysmography.
RegEM's processing time is increasing as the number of available measurements increase due to the inner mechanics of the algorithm which require multiple regression to take place.
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