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Searching for Content A semantic search engine is a remarkably useful solution. It can discover if two documents are similar even if they do not have any speci c words in common and it can reject documents that share only uninteresting words in common. Latent semantic indexing looks at patterns of words within a set of documents. Natural language is full of redundancies, and not every word that appears in a document carries semantic meaning. Frequently used words in English often do not carry content: examples include functional words, conjunctions, prepositions, and auxiliary verbs. The rst step in doing LSI, therefore, is culling these extraneous words from a document. This is called stemming.

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will be adopted from here on out Note the weights are commonly normalized to sum to 10, and the value functions are normalized to range from either 0 to 1, or 0 to 10, or 0 to 100 1341 Eliciting Value Functions The axioms of decision analysis produce the result that the value function over the vector x of bottom-level objectives must only be an interval function when the decision maker is risk neutral (the assumption made here) As a result, the individual value function vi over bottom-level objective xi must also be an interval-scaled function of x This interval property is the key to eliciting value functions from stakeholders about the relative value they assign to improving from the threshold of acceptable performance of xi, xi0, to the most desired value of xi*.

Grouping of practice sessions block versus random practice A common question among the coaching fraternity is whether it is better to practice a skill repetitively within a practice session, or whether it is preferential to mix up skills during the session. The former is often referred to as blocked (or massed) practice, while the latter is described as random practice. A typical blocked practice session involves athletes practicing one skill (more skills may be involved but they are practiced independently of each other) in a session with relatively low contextual interference (Battig 1979). Conversely, random practice sessions involve a multiple number of skills practiced simultaneously (or under tactical conditions) and present athletes with higher contextual interference (Battig 1979). Table 1.2 provides an example of the differ-

Watson and Buede [1987] present the bisection and the equal differences methods for eliciting these functions These value functions take four general forms (see Fig 131): decreasing returns to scale (RTS), linear RTS, increasing RTS, and an S-curve The decreasing RTS signi es a satiation of preference near the most desired value Decreasing RTS is commonly encountered when the threshold of acceptable performance is within the key performance range of interest to the stakeholders and the most desired value is outside this key performance range where satiation takes over The linear RTS is commonly found when both the threshold of acceptable performance and the most desired value are within the key performance range of interest, or when there is no possible satiation of preference.

The Engineering Design of Systems: Models and Methods, Second Edition. By Dennis M. Buede Copyright r 2009 John Wiley & Sons, Inc.

Preserve all registers. EAX, [ESP+32] : Push pointer to the return addr and params. ; Push pointer to byte encoded parameter info. ; Push pointer to the function's name. ; Call function that does logging. ; Restore original registers. [RealAddressOfInterceptedFunction] ; Jump to the original code. szFunctionName[] paramInfo[] ; ASCIIZ name of the function. ; Optional byte encoded parameter info. ; First byte is the length of the info. EAX [pParamInfo] [pszFunctionName] LogCall

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