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Obesity has become a challenging problem in public health.
In this era of big data, analyzing large scale data efficiently and accurately has become a challenging problem.
With the advent of SOC designs, testing and verification of the core-based designs become a challenging problem.
How to reduce the computational complexity of graph cut clustering to process the massive complex data has become a challenging problem.
With the fast development of high speed network of 100 Gbps and beyond, how to efficiently monitor and measure the network at flow granularity has become a challenging problem.
In particular, cooling represents approximately one third of the total electricity consumption, therefore efficiently cooling data centers has become a challenging problem and it represents an opportunity to reduce both IT energy costs and emissions environmental impact.
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Consequently, interpretation of the limited but valued data generated by the self-powered wireless sensing technology becomes a challenging problem.
As a result, how to design an efficient MAC in a solar energy harvesting based WSN becomes a challenging problem.
Therefore, the prediction of the vertex-induce vibration of slender cable suffered from multi-mode and high-mode motions becomes a challenging problem.
With the miniaturization, integration and functionalization of electronics and the emergence of new applications such as light emitting diodes, thermal dissipation becomes a challenging problem.
Cerebral white matter segmentation in brain Magnetic Resonance Imaging (MRI) data becomes a challenging problem due to a combination of several factors like low contrast, presence of noise and imaging artifacts, partial volume effects, intrinsic tissue variation due to neurodevelopment and neuropathologies, and the highly convoluted geometry of the cortex.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com