Sentence examples for data in the exploration from inspiring English sources

Aiming at solving the problems brought by the big data in the exploration, we present the parallel algorithm and the performance analysis combining Compute Unified Device Architecture (CUDA) with Open Multi-Processing (OpenMP) based on Graphics Processing Unit (GPU) accelerating.

With the ever increasing computational power, machine learning has become a popular tool to mine human data in the exploration of how people direct their gaze when inspecting a visual scene.

Well data (in the form of exploration wireline logs, cores, petrographic thin sections, major and trace element analyses) indicate that their syn-rift fill was dominated by abundant volcaniclastic sediment supplied through debris flows, hyperconcentrated flows and pyroclastic ash-fall.

Therefore today, machine learning, pattern recognition and data mining approaches became essential in the exploration of big data.

One of the most important geochemical data in petroleum exploration is total organic carbon (TOC) which is used to evaluate the hydrocarbon generation potential of source rocks.

We used waveform data obtained in the seismic exploration experiment with densely deployed seismometers that was conducted in and around Sakurajima Volcano in November 2008.

We propose that this study provides compelling in vitro data to justify the exploration and elucidation of the mechanisms of PAC-induced proliferation inhibition of oral cancers and for testing of PAC in animal models.

We introduce the theory of fuzzy cognitive maps (FCM) as a tool for the analysis of remotely collected data in planetary exploration.

This paper describes SVC model, which combine exploration data in the regional-scale for copper potential mapping in Kerman copper bearing belt in south of Iran.

The Oil and Gas Authority OGAA) has announced a major release of industry data in the hope of encouraging more exploration.

Cluster analysis is a powerful strategy for the exploration of high-dimensional data in the absence of a-priori hypotheses or data classification models.