You’ve been working with some physicists who need to study, as part of their experimental design, the interactions among large numbers of very small charged particles. Basically, their setup works as follows. They have an inert lattice structure, and they use this for placing charged particles at regular spacing along a straight line. Thus we can model their structure as consisting of the points {1, 2, 3, . . . , n} on the real line; and at each of these points j, they have a particle with charge qj. (Each charge can be either positive or negative.) They want to study the total force on each particle, by measuring it and then comparing it to a computational prediction. This computational part is where they need your help. The total net force on particle j, by Coulomb’s Law, is equal to

You will be given two character arrays of the same size, one will contain a number of ships. ships will move around the character array based on which way they are facing and the route they are on. routes are given in the other array. the route consists of '-' and '|' for straight paths, '\' and '/' for curves, and '+' for intersections. there are ships on these routes. ships always face a direction, '^' for up, '> ' for right, 'v' for down, and '< ' for left. any time the ships hit a '\' or a '/' it will turn as you would expect a ship to turn (e. g. a '^' that moves into a '/' will turn right). at an intersection, ships will always continue straight through. all ships move at the same speed, ships take turns moving and all ships move during one 'tick'. the one in the most top left goes first, followed by those to its right, then the ones in the next row. it iterates along the rows and then down the columns. each ship moves one space on its turn moving along the route. your function needs to return the position of the first collision between two ships and the number of ticks before the crash occurred.

Using least squares fitting, you are to fit the data sets to the following models and solve for the parameters ai , where i is the index of the parameter. the input/output data for the systems are linked in the bblearn site. for each of the systems use matlab to plot the supplied data vs. the model fit on one plot. include your code in the solutions. (a) linear fit "lineardata. mat" y=a1x^3 + a2x^2 + a3x + a4 (b) plant fit "plantdata. mat g(s) = a1/(s + a2)

Hey i just logged on and one of the moderators deleted a bunch of my answers to questions, even though the answers were right and the people it doesn't make sense but if anyone wants to talk about anything just message me lol (this is super random lol)