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Healthcare Consultation Center II (HCCII). The LTVS prototype was then evaluated with the results described in Sections 27.4.6 and 27.5. This section presents the cost analysis. Table 27.7 shows the cost of the LTVS prototype, including hardware and software installed at HCCII but excluding system design, software devlopment, implementation, and evaluation time. The cost of LTVS also includes the annual license fees for facial identi cation biometric system; purchased hardware and software are at an education discount price. 27.7 ALTERNATIVE IDENTIFICATION DEVICES 27.7.1 System Design To address the biometric veri cation component and determine which biometric system is the best for given applications in the complex clinical environment, the ngerprint scan system was added on the LTVS to run parallel with the facial recognition systems. Each solution was evalutated and documented for the advantages and pitfalls in the clinical environment. Figure 27.13 is a slight modi cation of Fig. 27.6 in whcih the ngerprint scanning system is added onto the FRS (facial recognition system) to become FRSS (facial and ngerprint recognition system). Because of the modular design of the LTVS, such a mdoifccaiton was not dif cult to accomplish.

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Project objectives:

An inode is a UNIX file system data structure that holds information about a directory entry. Each directory entry is uniquely identified by a device number and an inode number. Some of the following routines may return inode numbers; for UNIX machines these are valid, but for other platforms they are just dummy values.

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Despite what some managers occasionally seem to believe, a model isn t a silver bullet or enchanted wand that will magically make a project succeed A model by itself doesn t do anything It doesn t build a database, it isn t a piece of software (although there are software tools that can help you build a model), and the nal user of your database never sees a model A model is a plan It s a blueprint for building something, in this case a database The purpose of the model isn t to do anything by itself Instead it gives you a concrete way to think about the database that you are going to build By studying the pieces of the model, you can decide whether it represents all of the data that you need to meet your customers needs.

y annular-ring slot r1 d R patch substrate h air layer h A Wilkinson power divider with a 90o phase shift B feed substrate r ground d r2 x annular-ring slot patch r h1

The performance gains are quantified under two categories: interference avoidance gain (IA) and traffic diversity (TD) gain. The algorithm implemented by the RNC captures IA gain and partial fading diversity gain since no traffic feature is accounted. The IA and partial fading diversity gain exploited by the RNC can be quantified by the performance comparison between RNC and RAND. On the other hand, the algorithm implemented by BSs exploits both traffic diversity gain and some fading diversity gain. The T D gain and partial

The iteratively reweighted least squares step AtIRLs for estimating the parameters of the expectation model supposes the elements of the covariance matrix C of the observations to be known functions of the parameters 8. This known dependence is used in the step

A model is also useful for ensuring that everyone on the project has the same understanding of what needs to be done If everyone understands the model, then everyone should have the same ideas about what data should be stored, which tables should contain it, and how the tables are related They should also agree on the business rules that determine how the data is used and constrained Note that it s important that everyone actually understands the model I ve seen developers build remarkably complicated models and then dump them on hapless end users, expecting those users to understand the models every subtle nuance The developers ended up walking the users through the models until the users heads were spinning and the developers could have convinced them of just about anything The models are for those who know how to understand them, not necessarily for everyone.

with o the N x 1null vector. This shows that both first columns of ag(B)/aeT are linearly dependent and, hence, that this matrix is singular. Note that this singularity is related to the expectation model only and not to statistical properties of the observations. rn

Now it s time to create the first item element, give it a type attribute with the value fruit , and add the element to the stockList element:

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