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Fundamentally, any pattern recognition problem can be broken into a set of three functions: focus of attention, clutter rejection, and identi cation. The identi cation step accesses the system s knowledge base to compare the unlabeled entity features to those in the system s library. The result is a decision with the associated con dence (Figure 17.23). For cardiac function, focus-of-attention is performed by the single clock timing all of the modalities and the segmented ECG heartbeat timing applied to pulse oximetry and blood pressure. The synchronized Phase 1 data provides the inputs for this analysis. Numerically all the attributes were of the same magnitude. Fusion was performed over 16 individuals.

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Component properties are stored in the This scope inside the component, but This is a public scope, so it can be both read and modified by code outside the component. This-scoped variables (properties) are exposed in a CFDUMP of the component instance, which is very convenient for visualizing and debugging behavior, but if you want to create properties that are truly local to the component, you must forego using the This scope in favor of what is sometimes called the Unnamed scope.

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By eliminating an explicit prefix from variables declared inside a component, you make those variables private to the entire component, and these variables persist for the life of the component. If you CFSET a variable named myVar in the Unnamed scope within a component function and then CFSET myVar inside a different function within the same component, you are setting the same variable, as it pertains to the entire component and not just the function in which it is declared. The setter and getter functions in Listing 23-18 treat variables in the Unnamed scope as local properties, even though they don t show up in a CFDUMP of the component instance.

<cffunction name= SetMyName access= public returntype= void output= No > <cfargument name= MyName type= string required= yes > <cflock name= #This.lockName# timeout= 10 throwontimeout= Yes type= EXCLUSIVE > <cfset myName = Arguments.MyName> <cfreturn> </cflock> </cffunction>  <cffunction name= GetMyName access= public returntype= string output= No > <cflock name= #This.lockName# timeout= 10 throwontimeout= Yes type= READONLY > <cfreturn myName> </cflock> </cffunction>

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The biggest problem facing the pattern recognition task is clutter rejection, or false-positive responses. Multimodal fusion has been shown to reduce false acceptance rate (FAR) in addition to improving probability of detection (Pd) [50]. There are three basic techniques for fusing data [51]: combining attributes, merging decisions, and voting (Figure 17.24). Combining attributes is a straightforward fusion technique. With combining attributes, a single identi cation algorithm is generated using feature vectors containing all of the attributes [52]. In other words, the feature vectors from all modalities are concatenated to form a new features vector, which is fed to the classi er. When we combine attribute techniques, we assume that the identi cation algorithms can handle (a) a relatively larger number of inputs and (b) possible differences in the input format (i.e., real, nominal, ordinal, etc.,), and we also assume that the attributes are registered and synchronized. Decision fusion occurs when a set of classi ers generates a score from each sensor s attributes. The outputs from the individual classi ers are amalgamated using various weighting parameters based upon their belonging or membership to each output [53]. In this case, the scores were amalgamated twice: once by adding and the other by multiplying the corresponding scores from the individual analysis. Decision fusion is ideal for cases when sensor data are of different types or formats and in cases when an interaction across modalities is not expected [54]. Voting fusion is a simpli cation of decision fusion. With voting, each classi er makes a decision that is, votes on the assignment for each input record generating a rank. Final assignment for each record is based the majority of output decisions [55]. Voting fusion was performed by multiplying the ranks of the

Our personal preference is to use This-scoped properties and just be very careful about our coding because we like the capability to inspect all aspects of our components as they execute, but the choice of which scope to use for your component properties is entirely up to you.

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