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3D geological modeling has involved the complexity of two aspects: data and models.
In this paper, we focus on four aspects: data volume, prediction correctness, service variety, and information protection.
The Belgian Hudem project involves different workgroups each focusing on different aspects: data fusion, sensor development and sensor positioning.
Generally, data-driven based fault detection consists of the following aspects: data measurement, data processing, data comparison, and data assessment [1].
Adapting actively unique characteristics of GPU software and hardware, the proposed GPU algorithm is optimized from four aspects: data transmission, parallel task allocation, memory access, and CUDA (Compute Unified Device Architecture) stream.
The study uncovers state-of-the-art approaches in research methodologies in IB in terms of five major aspects: data collection methods, sample sources including sampled countries and subjects, sampling methods, sample sizes, and response rates.
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The focus of this analysis is to identify the surveys and taxonomies for cloud computing resource management focusing on five aspects: data-intensive loads, dynamic management, reliability, hybrid/multicloud scenarios, and workflow management.
Topography (elevation, slope, and aspect) data were retrieved from the U.S. Geological Survey (USGS National Elevation Datasett [32].
In the paper, we present a multi-aspect data analysis approach for investigating human computation mechanism.
Residual values for the model exhibited little apparent bias against any of the variables included in the model or aspect (data not shown).
The Australian introduced range and the 39 Australian occurrence points were omitted from this analysis because slope and aspect data were not available for that region [52].
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