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Define each level of Maslow's hierarchy of needs. For each of the five levels, briefly describe a marketing message appealing to this need level.
Consider a system where items arrive according to a Poisson process with parameter ? = 2 item/sec.
Conversely, each shock may break down the system with probability 1 - a. Find the probability that the system is still running at time t.
Consider a system where items arrive according to a Poisson process with parameter ?. Items are collected in a storage facility that can host up to Q objects.
Say which of the following processes is a discrete-time MC. Motivate your claim.
Find the asymptotic and/or stationary state probability vector, if it exists.
For a generic function g(n) defined for n = 0, we define its z-transform as.
Consider the discrete-time MC with transition matrix.
Classify the MC and determine the asymptotic probability vector, if possible.
Determine the asymptotic state probability vector of the MC with infinitesimal generator matrix.
Draw the state flow diagram and determine the time-dependent behavior of the state probabilities for such a process.
Comment on the existence of the asymptotic state distribution. Find the asymptotic state distribution vector p.
Doing business in foreign markets has its pros and cons. What are some of the difficulties in doing business in a foreign country?
Consider a variation of the SMUX device of Problem 7.20 in which packets are generaed and get served in pairs.
The distribution of the number of bolts fixed in each run, that is, in the interval between two consecutive repairs;
We wish to determine the asymptotic percentage of stuffed bits in the message transmitted over the line.
Consider a wireless system where a random number of mobile users share a common transmission channel with capacity of C = 1 Mbit/s.
Which of the following properties apply to an infinitesimal generator matrix Q?
Prove that w(t) is a (two-dimensional) MC. Write the probability flow balance equations.
That the repair takes an independent random time with exponential distribution with parameter ?. Compute the asymptotic probability of the working state.
Let x a Gaussian rve with mean vector and covariance matrix.
Show that the probability P [x > 2] as a function of is continuous and monotonically increasing.
Consider a terminal randomly placed within such a cell, so that with x and y the spatial coordinates of the terminal with respect to the base station.
Consider K independent rvs yk, k = 1, 2,...,K, with exponential distribution of parameter.
Let y1, y2, ... iid rvs with exponential distribution of parameter ?. Let x be a discrete rv defined as follows.