In this project the behavior of the Faraday cage as an insulator against an induced load, either by an effect of nature as lightning or lightning or power surges be considered. As we know the Faraday cage is a conductor of electric current and therefore theoretically there will be inside a magnetic field or electromagnetic wave in the same way there will be no magnetic field.
Deep learning is a fast growing field in tech that is often described to have limitless potential. This paper describes its history, why the explosion in popularity, and how it works. An example of classifying images of handwritten digits (MNIST) will be explored using a fully connected network and a convolutional neural network. Next, a brief description of the tools necessary for the reader to implement his or her own network. Finally, a view of the state of the art being developed by companies such as Google, Facebook, and Baidu.
In this paper we propose a first version for a computational proposal for Electromagnetic Field (EMF) Pollution for the construction of calculated maps, as a visualization tool for estimating the levels of human exposure to potentially harmful levels of electromagnetic radiation. The computational model includes the necessary mathematics for estimating levels of exposure in any two dimension space point in a map, given a massive set of emitters and its relevant parameters, but also contains adjust considerations using a data set of field measures that would allow the model to adapt to real environmental conditions. This combination of mathematical model and field data also will allow us to skip the use of interpolations an other statistical methods typically used in maps based exclusively on measures. The proposal also specifies the system main features and development methodology in order to achieve an interactive and flexible tool.