An approach to connecting corresponding points between every two adjacent measuring trajectories is proposed to formulate triangular meshes directly from the massive data points, so as to determine the normal vector of each point for probe-radius compensation.
Somewhat surprisingly Greenpeace sort of applauds the virtues of living in a massive data cloud, pointing to the advent of the smart grid and increased amount telecommuting.
In many important examples, network structure is imposed as a topological framework for enabling the useful visualization and subsequent analysis of a dataset (often "massive") whose data points come a priori not as a network, but rather with a notion of similarity (or dissimilarity) between them.
This problem appears recurrently in reverse engineering, where a set of (possibly massive and noisy) data points obtained by 3D laser scanning have to be fitted to a free-form parametric curve (typically a B-spline).
With the massive number of data points now being monitored in gene and protein expression assays, some stakeholders are concerned that changes in gene expression or protein levels will be mistakenly interpreted as related to adverse effects when in fact they are benign.
As illustrated in Fig. 6, a distributed simulator for fault response of power systems according to previous study [31] serves to generate massive data samples based on the given operation point in a parallel computing environment.
Such demand will soon result in large-scale clinical sequence datasets requiring massive data analysis and interpretation at reimbursable cost points thereby producing a technological barrier and price-limiting step of clinical genome usage [ 3, 4].
For decades, carriers worried about getting calls from point A to point B. Now they have to worry about tethering, massive data downloads to small devices, and always-on connectivity.
In this talk, we address some general aspects of massive data access in the GRID environment, considering them from the point of view of some High Energy Physics experiences in large scale computing.
This volume discretization method improves the efficiency of the process since it is defined by a much more simple conception by means of massive data storage arrays whose elements are the coordinates of the part boundary points.
