The phrase "application in a broader" is not complete and lacks clarity in written English.
It can be used when discussing the wider implications or uses of a particular application or concept, but it needs to be part of a more complete thought.
Example: "The application in a broader context reveals its potential impact on various industries."
Alternatives: "application in a wider context" or "application in a larger framework".
We have then described a policy model putting this application in a broader research policy context to demonstrate that an isolated metadata sharing policy is superior to an isolated data-sharing policy, and that both policies combined achieve the best results in terms of publications, thus emphasizing the important role of the DoD in this context.
The overall acceptance of this type of application in a broader CKD population remains unclear, as does its utility in improving adherence or disease outcomes.
By virtue of its applicability to time-varying and nonlinear systems, adaptive signal processing finds application in a broad range of practical fields such as telecommunications, radar and sonar signal processing, biomedical engineering, and entertainment systems.
These unique properties are being exploited to create new diagnostics and therapeutics for application in a broad spectrum of organ systems.
The examples shown demonstrate the advantages of the technique for high-resolution NMR, but we expect the approach will also find application in a broad variety of areas including imaging and in vivo spectroscopy.
It explores emerging technologies and their application in a broad range of engineering disciplines, including communication technologies and smart grids.
We use the term 'knowledge application' in a broad sense which implies both, knowledge acquisition and knowledge application in the sense of Greiff et al. (2013a).
Outlier detection has immediate application in a broad range of contexts, particularly, for machine learning techniques, effective decision on the observations with categorizing them as normal or outlying are important for the improvement of learning performance.
All these devices may be able to perform certain functions but may be limited to their application in a broad way.
Here we have shown its application in a broad range of physiological signals including epileptic seizure data, EEG data with very low frequency characteristics, MEG data and evoked response recordings.
The field has applications in a broad range of areas ranging from finance to transportation to energy optimization.
