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The proposed algorithm utilizes a robust data-filtering procedure that identifies valid data within a dynamically varying validity window.
Their criticisms are abundant and of varying validity.
Firstly, different types of contextual data have varying validity durations i.e. a certain scope of context information (location, activity, Wi-Fi, weather, etc).
Consequently recommendations and guidelines of varying validity and quality have been published, often failing to convince the medical, insurance and government worlds to support nutritional care.
The Danish Registry of Causes of Death has varying validity for different causes of death, although it is almost complete for cancer deaths [ 16, 24, 25].
Nevertheless, depending on the respondent's degree of involvement with the specific events under consideration, these views are likely to be of varying validity in relation to providing an account of the key actions.
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However, different types of contextual information have varying temporal validity durations and a varied spectrum of access frequencies as well.
Previous studies have attempted to validate other data from form CMS-2728, resulting in varying levels of validity and reliability [ 31- 33].
At the same time, varying completeness and validity of the individual variables underscore the need for validation of its clinical data before using the registry for research.
The validity of the Danish National Registry of Patients as a source of information on comorbidity and venous thromboembolism has varying completeness and validity for different diseases.
However, the results are varying and the validity of results from small-scale fatigue tests for real structures is sometimes unclear.
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