The previous state-of-the-art systems required large amounts of task-specific knowledge in the form of feature engineering, lexicons and data pre-processing to achieve high performance.
This results that large amount of computational tasks is reduced into limited simple calculation in modified FGP model formulation.
The low signal-to-noise ratio of the images leads to a large amount of low-level tasks in order to meet the accuracy requirements.
When a mobile node running Map tasks has significant delays in transmitting a large amount of intermediate result to Reduce tasks through wireless connections (i.e. tasks are running slower than expected due to the lengthy transfer time of Shuffle phase), the Master launches another, equivalent tasks as a backup instead of diagnosing and fixing the slow-running tasks.
In addition, a powerful base station [14] is used for centralized scheduling to perform a large amount of computation and communication tasks, and it is dificult for the base station to maintain the global information of the whole network, which will lead to a large amount of data transmission, and thereby cause more energy consumption.
However, non-stationary vibration signal with a large amount of noise makes this task challenging.
If one has a large amount of genomic data, the task of identifying first degree relationships, i.e. parent offspring and full-sibs relations, is trivial.
The texture analysis of multiple subjects can be performed automatically without user intervention, which is extremely helpful for processing a large amount of data, an unavoidable task for future studies aiming to evaluate the heterogeneity quantification of molecular images.
The goal of MapReduce is to deploy a large amount of time- and memory-consuming tasks to all computing nodes that process tasks in parallel by user-defined algorithms.
In our pilot study we found signs of inefficient use of staff time in clinics with small number of patients, resulting in relative large amount of staff time spent on indirect tasks such as reporting and recording and other administrative tasks.
