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The phased life cycle approach gives businesses more time to understand and assess future requirements and to make changes during the actual implementation phase In addition, a phased approach gives the client quick wins, even at the very first phase..

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Figure G.3 illustrates transducer power gain. The input power pin is still the power that the source delivers to a load that is matched to the source. The output power pout is the power the module delivers to a speci ed load when the module is driven by the source. Both source and load must be speci ed (50 real is usual). From the de nitions of the S and T parameters and the normalized waves

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Pharmacogenomics may help to explain much of the variation in response to medications, but it will not explain all of the difference. Drug interactions, age, nutrition, renal and liver function, and a variety of environmental factors in uence the essential pharmocodynamics and pharmacokinetics of drug response (Evans and Relling, 1999; Omenn, 2001). Thus, to understand the role of genetic factors, it will also be necessary to study the effects of environmental factors, both individually and in combination. Only with greater knowledge about the role of both genetic and environmental factors will it be possible to develop drug response pro les for individual patients as well as patient-speci c prevention strategies. The National Institute of General Medical Sciences (NIGMS) of the NIH has initiated the Pharmacogenetics Research Network focusing on the study of how genes affect the way people respond to medicines. NIGMS de nes the ultimate goal of pharmacogenetics research as helping physicians tailor doses of medicines to a person s unique genetic makeup, thereby making medicines safer and more effective for everyone. Information regarding pharmacogenetic research is available at http://www.nigms.nih.gov/pharmacogenetics/index.html. The National Institute of Environmental Health Sciences (NIEHS) within the NIH is the lead institute for the Environmental Genome Project (EGP). Relying on technology developed by the HGP, the goal of the EGP is to identify polymorphisms of environmental disease susceptibility, develop a central database of these polymorphisms, and foster population-based studies of gene-environment interaction in disease etiology (NIEHS, 2001). Although the EGP is more concerned with toxicology than pharmacology, broad scienti c understanding of gene-environment interaction will have widespread applicability, including in pharmacogenomics. Additional information regarding progress of the EGP is available at http://www.niehs.nih.gov/envgenom/home.htm.

The Wideband Delphi approach relies on multiple meetings of individuals involved in the project and a progressive convergence of their effort estimates. Estimation by effort analogy is based on data from similar existing projects or a working prototype of the current project, which are used as the basis for the total project effort estimation. Parametric models are mathematical representations of formulas with variables for effort-related factors such as project complexity, required product reliability, organization maturity, component reuse, and many more. These models use regression analysis, numerical analysis, or management surveys to calculate parameter values. For small projects, simple heuristics based on the product design and developers estimated time of effort should suf ce. For medium to large projects (those that exceed $1M in costs), it is recommended that two complementary approaches be used to verify the validity of the estimates. The project effort estimates are readjusted throughout the project s lifetime. Thus, they are a changing component of the SDP document, which is modi ed and validated based on the progress status of the tasks de ned in the project s initial and subsequent iterations of product development.

14.5 CONFIDENCE LIMITS The mean and standard deviation of the field intensity are calculated at each far-field point using the general PDF in (14.45). Figure 14.7 show the error-free pattern of an array. Figures 14.8a c show mean and 1 boundaries of the far-field intensity for three different sets of parameters. The mean performance deteriorates with increasing uncertainties in amplitude and phase. In addition, the 1 range becomes wider as the amplitude and phase uncertainties increase. An important parameter is the 95% confidence limit for the far-field intensity. At the beam peak location this limit is defined as the threshold intensity where the array has 95% probability to exceed the threshold. This definition of confidence limit changes for side lobes and nulls. For a side lobe (or null), this limit is defined as the threshold intensity where the array has a probability of 95% not to exceed this threshold. We will consider the 95% confidence limits for three important cases.

Dimensions, Attributes, Levels, and Hierarchies The CWM Model Defining the Dimensions and Attributes Defining Levels and Level Attributes Defining Hierarchies and Hierarchical Attributes Add the Dimensions to the Schema Defining Cubes and Measures Add the Cubes to the Schema Defining Keys Adding Keys to the Dimensions Adding Keys to the Levels Adding Keys to the Hierarchies Adding Keys to the Cubes

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