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How to reduce the size of the System Volume Information folder? 

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Papers (17)Insight
Open accessBook ChapterDOI
01 Jan 2018
48 Citations
It is therefore of paramount importance to be able to reduce the size of the dataset in the feature space.
Hence, the size of the computational volume can be reduced to a minimum.
Thus, both the data volume and the information detail increase dramatically.
In addition, MSI can also reduce the storage size of the dataset.
Therefore, it is possible to reduce power supply volume.
The model suggests that a significant increase in the sulfate reduction capacity of the system is possible by increasing the volume of the bed relative to the total liquid volume of the system.
If we can reduce the size of input data without loss of information, we can speed up such a heavy process.
The reduction of logistical volume can reduce the overall pressurized vehicle mass directly, or indirectly benefit the mission by allowing for an increase in habitable volume during the mission.
However, when dealing with enormous data volume, its performance may drastically reduce.
Thus, the cost and volume of the system can be reduced.
Integration techniques can be used to improve space utilization and reduce the total system volume.
Finally, we show that it may be possible to reduce the size of a surveillance system without affecting the quality of surveillance information produced.
The proposed method succeeds to reduce the size of bus component several times without compromising the system performance.
It is thus possible to reduce the size of the stored test set even further.
With regard to this, the results obtained for the alternative control system show a 20% reduction of the volume of the tank, given a certain level of comfort, and is therefore useful to reduce the size of the storage tank.
Moreover, the proposed approach captured the effect of the complexity and overall size of the system, showing the relevance of this performance indicator for evaluating technologies for applications in which volume is a limiting parameter.
The developed tool gives useful information to appropriately size the compression system and to manage it in the most effective way.