There are several limiting factors to traditional approaches to big data processing, including time-intensive manual query and analysis.
Kaushik and Bhandarkar (2010) proposed an energy conserving hybrid multi zone variant of HDFS for intensive data processing, commodity Hadoop clusters.
General purpose computing on graphics processing units (GPUs) has been previously shown to speed up computationally intensive data processing and image reconstruction algorithms for computed tomography (CT), magnetic resonance (MR), and ultrasound images.
Computer Vision is one of the most intensive data processing fields, and conventional systems do not provide any mechanism to address adequately this task, so this issue comes up as an important drawback.
To demonstrate F l u χ feasibility, usefulness, and efficiency, the assessment of F l u χ was centered on a realistic prototypical example of intensive data processing, addressing the evaluation of air quality, pollution and health risks, for a city based on sensory data, gathered asynchronously, from thousands of sensors.
For better performance, store efficiency and intensive data processing, the BAM file, a binary representation of SAM, was implemented.
Since these data processing techniques are computationally intensive, we have adopted a method that removes all data with such artefacts since the number of bad pixels in an image is still very small (< 1%).
In a study carried out in the United Kingdom to evaluate musculoskeletal disorders and visual strain in intensive data processing workers, 86% of data processors reported musculoskeletal pain/discomfort in the previous year, with the highest prevalence rate (58%) found for the neck [ 21].
Furthermore, there are still needs and the opportunities to bridge the technical domains of large-scale data processing ("Big Data"), data-intensive sciences and the applications, and the high-performance computing.
One advantage to using digital channels in lieu of face-to-face interviews is of course faster, less resource-intensive data processing.
However, the required computational cost is high due to intensive image data processing.
