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Cloud-BLASTP takes advantage of high performance, availability, reliability, and scalability.
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The features of Hadoop BLASTP are high performance, availability and reliability, and scalability.
These issues can be addressed through the development of new or improved storage technologies with higher performance, availability, durability, safety and lower costs.
However, the selective laser sintering (SLS) availability of high performance PA6 is not thoroughly investigated.
The growth of smart grid is dependent on the availability of high performance computing (HPC) and analytics technology to process a massive amount of data set.
Despite the availability of high performance glass technologies a preconceived idea that glass is the weak point in a building envelope still persists [1].
Recent availability of high performance computers and computational methods along with continuing increase in operational experience necessitate revising some operational constrains and conservative safety margins.
The work here is directed at examining a model predictive control (MPC) implementation that takes advantage of recent advances in the availability of high performance computing platforms at modest cost.
However, given the common availability of high performance computing platforms, it is becoming feasible to apply computationally intensive calculation methods that sample millions of q-points to the simulation of polycrystalline models of increasing complexity, a technique referred to as poly-CINS analysis.
Clearly, the main reason is the missing availability of high performance separation and detection techniques in former times, but other reasons, e.g., focus on specific research interests, have to be considered also.
Whilst netballers were recruited from the same source to maintain a homogenous sample, access to and the availability of high performance netballers was limited.
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