Hijackers Use Boolean Network to Change Program Codes Flight Patterns from Igari to Gival Route P628 on MH 370
view-source-www-flightradar24-com-data-airplanes-mh-370.png &#xf178 computer language missing malaysia airline
the idea girl says
all this from a google number in code – 
I was thinking flight 178 but this shows us something entirely different.
the idea girl says
time to educate ourselves on what all this program jargon means, I hope it will lead us to where flight MH370 is and we are going to find it using remote viewing and all those responsible for it’s hijacking and the other planes and helicopter crashes they have been doing since 2007. yep, there’s more to come in the data.
learning how to read it now, so I can blog what it means so you can help too!
A Boolean network consists of a discrete set of Boolean variables each of which has a boolean function (possibly different for each variable) assigned to it which takes inputs from a subset of those variables and output that determines the state of the variable it is assigned to. This set of functions in effect determines a topology (connectivity) on the set of variables, which then become nodes in a network. Usually, the dynamics of the system is taken as a discrete time series where the state of the entire network at time t+1 is determined by evaluating each variable’s function on the state of the network at time t. This may be done synchronously or asynchronously.
A Boolean network is a particular kind of sequential dynamical system, where time and states are discrete, i.e. both the set of variables and the set of states in the time series each have a bijection onto an integer series. Boolean networks are related to cellular automata. Usually, cellular automata are defined with an homogenous topology, i.e. a single line of nodes, a square or hexagonal grid of nodes or an even higher dimensional structure, but each variable (node in the grid) may take on more than two values (and hence not be boolean).
A random Boolean network (RBN) is one that is randomly selected from the set of all possible boolean networks of a particular size, N. One then can study statistically, how the expected properties of such networks depend on various statistical properties of the ensemble of all possible networks. For example, one may study how the RBN behavior changes as the average connectivity is changed.