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10.4.1.1 Capture the Requirements In this rst step, we attempt to capture the requirements using some standard technique. Typically, we use a series of questions, interviews, facilitated sessions, and so on to build a description of the problem and proposed solution. Often we will use techniques like Structured English, State Diagrams, and Use Cases based on the software development processes followed within our project. While the more sophisticated techniques can be very useful, often the Structured English approach is the easiest to understand and implement. Structured English is merely an attempt to capture requirements in a more formalized and uniform sentence structure and vocabulary. It tends to be very repetitive, unimaginative, and boring to read (and to write), but it has the advantage of removing ambiguity and easily identifying similar patterns within the requirements. Sometimes we will even use high-level ERDs to help capture these details showing some (not all) of the possible ETs and RTs without all the other details (such as ATs, cardinalities, and role names) that a real ERD would require. These high-level ERDs are merely short-hand notation and not intended to be anything more than simple reminders of the basic structures

Moreover, the degree of delivery redundancy is controlled, as paths are expanded quickly from the source, maintained within a reasonable width next, and nally shrunk near the sink Tilak et al [50] trade accuracy of information for energy saving in data dissemination They advocate nonuniform information granularity, that is, the required accuracy of information decreases as the distance from the source becomes longer Applications in the battle eld or disaster rescue scenarios usually possess such characteristics Two deterministic and two nondeterministic protocols are designed for nonuniform information dissemination The proposed protocols trade.

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With a 2-ml sterile pipette, take out a medium sample, e.g., for determination of secreted proteins. (e) With a Pasteur pipette, aspirate medium until the liquid level equals the 75 ml mark. Avoid touching the scaffolds with the pipette. (f) Add 75 ml fresh medium either control medium or osteogenic medium with a double concentration using a 25-ml pipette. (g) Close the screw cap. (h) Put the spinner ask back into the incubator. (i) Unscrew the screw cap for aspiration; do not open completely to avoid contamination. (j) Stir at 60 rpm.

Cells harvested at the end of the rst passage (or later passages if an insuf cient number of cells is available at the end of the rst passage) are used for the assays that are deemed appropriate. In our laboratory, highest priority is given to loading ceramic cubes for implantation. We do this for two reasons. First, as indicated above, we regard this as the de nitive assay for stem cells. The second reason is a practical matter relating to the length of the in vivo assay (6 weeks in vivo plus time for histologic processing and evaluation) and the time that companies that provide serum are willing to hold the product on reserve. Because we are usually pushing the limit of the reserve time, we try to get the cubes implanted as quickly as possible. Additional cell preparations may be needed to provide enough cells to complete all of the required assays, and because duplicate or triplicate data sets are desirable. Among the other assays that we routinely include in the testing of FBS for human MSCs are the in vitro assays for osteogenesis and chondrogenesis. For the former,

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Sanov . Let Xi be i.i.d. N (0, 2 ). 1 (a) Find the exponent in the behavior of Pr{ n n Xi2 2 }. i=1 This can be done from rst principles (since the normal distribution is nice) or by using Sanov s theorem. 1 (b) What do the data look like if n n Xi2 That is, what i=1 that minimizes D(P Q) is the P Counting states. Suppose that an atom is equally likely to be in each of six states, X {s1 , s2 , s3 , . . . , s6 }. One observes n atoms X1 , X2 , . . . , Xn independently drawn according to this uniform distribution. It is observed that the frequency of occurrence of state s1 is twice the frequency of occurrence of state s2 . (a) To rst order in the exponent, what is the probability of observing this event (b) Assuming n large, nd the conditional distribution of the state of the rst atom X1 , given this observation. Hypothesis testing. Let {Xi } be i.i.d. p(x), x {1, 2, . . .}. Consider two hypotheses, H0 : p(x) = p0 (x) vs. H1 : p(x) = x p1 (x), where p0 (x) = 1 and p1 (x) = qp x 1 , x = 1, 2, 3, . . . . 2 (a) Find D(p0 p1 ). (b) Let Pr{H0 } = 1 . Find the minimal probability of error test for 2 H0 vs. H1 given data X1 , X2 , . . . , Xn p(x). Maximum likelihood estimation. Let {f (x)} denote a parametric family of densities with parameter R. Let X1 , X2 , . . . , Xn be i.i.d. f (x). The function

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