It is essential to understand the particular tools and techniques that attackers use to take advantage of the unique way wireless networks are designed, deployed, and maintained.
Services provided by modern organizations are usually designed, deployed, and supported by large-scale IT infrastructures.
In this work, we propose Kuaa, a workflow-based framework that can be used for designing, deploying, and executing machine learning experiments in an automated fashion.
In addition, natural disasters like floods or earthquakes may impact the existing communication infrastructure (both fixed and wireless) with the consequence that wireless communications may not be available to PPDR organizations in the area of the crisis and alternative solutions must be designed and deployed.
The presented study is an analysis of what problems and difficulties most DNS administrators might encounter and provides the insights into how various DNS assistant sub-systems could be designed and deployed to solve the complex problems or alleviate these DNS administration job loadings.
While decision-making algorithms are inherently not biased and algorithmic decision-making depends on a number of variables -- including how the software is designed, developed, deployed and the quality, integrity, and representativeness of the underlying data sources -- there is a need for a new approach to define and design decision-making algorithms.
We have prototyped and evaluated our solution with an operational stack of a cloud delivery service that has been designed, commercially deployed and is in production to support millions of connected devices.
It can be designed to deploy "a variety of decontamination fluids, both gaseous and liquid," depending on which chemical or germ has been released.
Ambient data sensing devices are designed and deployed in water and waterless transportation facilities by which the simulation of real live transportation is tested.
Of course, the analytics processes had to be designed, developed, tested, and deployed by people.
