Sentence examples for more detailed datasets from inspiring English sources

The proposed method can clearly benefit from higher resolution remote-sensing data and more detailed datasets on soil properties and characteristics and is expected to provide a useful tool in planning and prioritising the works that are required for the mitigation of post-fire hazards.

Using imaging, the phenotype(s) of each cell in a well are recorded, producing much richer and more detailed datasets.

Reporting was likewise more concise and simple something that could be explained in a journal length article, with more detailed datasets available on request.

In order to carry out future research, more detailed datasets combining disaggregated immigration statistics and happiness are necessary.

But to go beyond the safety audit function and start trying to effect concrete changes such as those seen in Indian cities, D'Silva says they would need "a partner on the ground in those places because it's important for them to get a more detailed dataset" and to take a lead in advocating solutions that suit each local context.

A more detailed dataset would be needed to explore the choices and consequences of people's location choices, and reasons for (not) moving.

We investigate a more detailed dataset in an attempt to distinguish between these hypotheses.

Furthermore, the fingerprinting classification method requires more detailed training datasets as region sizes are reduced, which is time and labor consuming, and results in increased computation time in both the training phase and localization phase.

By generating more detailed molecular datasets for Hemerocallis, in tandem with biomedical studies of greater resolution to identify the active compounds responsible for therapeutic effects, Hemerocallis could be transformed into a substantial resource for the discovery of novel pharmaceuticals.

The tool is designed to accommodate various accuracy levels of tsunami exposure data which will support the users to undertake preliminary tsunami risk assessment from the existing data with progressive improvement with the use of more detailed and accurate datasets.

A more detailed list of datasets is provided in Additional file 2. We have used the machine learning library WEKA [34] (v3.7.13) for modeling and selected three well known classifiers: random forests [35], naive Bayes [36] and support vector machines [37].