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4 explores the complex challenges that nanotechnology poses for the EPA. Environmental groups have voiced concerns that nanosized particles, because they have different properties than bulk materials of the same substance, could present a host of new health and environmental hazards. However, since environmental laws require regulation of new chemicals and nanomaterials are just smaller versions of existing chemicals, these substances are starting to enter the environment with minimal regulatory review. We engage in a comprehensive analysis of the toxicity risks associated with nanomaterials and weigh these risks against the benefits. Ultimately, we conclude that, while more data is needed, the current data dictate that EPA should not subject nanomaterials to prohibitively stringent regulations. The EPA should first garner more data and consider subjecting nanomaterials to additional review procedures.

GLUE has a Content Learner and Name Learner, and a Meta Learner. The Content Learner exploits the frequencies of words in the textual content of an instance in order to make predictions and uses the Na ve Bayes s theorem. The Name Learner uses the full name of the input instance. The Meta-learner combines the predictions of base learners and assigns weight to base learners based on how much it trusts that learner s predictions. For ontology mappings between source ontology and integrated global ontology, an example tool is Learning Source Description (LSD). In LSD, Schema can be viewed as ontologies with restricted relationship types. Therefore, the mediated schema can be considered as a global ontology. The LSD system uses a multistrategy learning two phase approach: training and matching. In the matching phase, prediction combiner combines meta-learner s prediction and match the schema of new input source to the mediated schema. This process can be considered as ontology mapping between information sources and a global ontology. For ontology mapping in ontology merging, alignment, and integration, an example tool is OntoMorph. OntoMorph provides a powerful rule language for specifying mappings, and facilitates ontology merging and the rapid generation of knowledge base translators. It combines two syntactic rewriting and semantic rewriting. Syntactic rewriting is done through pattern-directed rewrite rules for sentence-level transformation based on pattern matching. Semantic rewriting is done through semantic models and logical inference.

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3. P

Professional services technology staff must consistently deliver systems, services, process improvements, and capabilities to meet the firm s needs and support its strategic objectives These must be done fast, right, and cheap, with success as the only benchmark To achieve this success, a firm cannot allow project teams to continuously reinvent the wheel A firm should have a preset project framework to guide project teams from inception of an idea to the closing celebration It should work to follow project management best practices It should provide form project documents with standard processes to follow It should divide its projects into quick wins (described later in the chapter) to deliver consistent and incremental improvements in manageable chunks Project management is not as interesting as knowledge management Project management is not as sexy as portal technology Project management is not as fascinating as a new operating system.

Yet, project management is necessary for any of these systems to be delivered successfully BASF Corporation, a major chemical company, had a well-advertised motto: We don t make the products you buy, we make the products you buy better The same can be said of project management Most often, project management does not make the products you use at your firm, but properly run projects make your use successful So, project management is about properly implementing knowledge management technology It is about creating valuable portal technology It is about implementing new operating systems In fact, project management is about any incremental change made Accomplishing this requires a project framework This is a process that helps project managers evaluate and execute their projects and ensures certain rigor along the way.

An incident linearly polarized plane wave, in the x-direction, can then be written as Einc( x ) = E0 a x eikz = ( E+ + E ) 2 (6.125)

A good starting point for developing a framework is Microsoft s web site, where it offers significant information on its recommended MSF While the complete MSF is likely too extensively documented and too rigorous a process for most professional team projects, it is an ideal starting point for developing a more streamlined process to fit a particular firm s culture and needs A framework formalizes a project management process and jargon MSF includes five phases: (1) envisioning, (2) planning, (3) developing, (4) stabilizing, and (5) deploying Being told that a project is in the envisioning stage tells you a lot as long as the definition of envisioning and the processes in that stage do not change from project to project MSF has predefined roles that project team members fill and that have predefined responsibilities.

3.1 Balanis provides a way to calculate r, eff for a microstrip of certain dimensions. For a trace width w = 0.010 , height h = 0.006 , thickness t = 0.001 and a nominal r = 4, the resulting value of r, eff 3.055. In this case, show that the constants in front of the square bracket to be 148 ps. Thus, for a microstrip TDin, LL ( microstrip ) 148ps 1 + (1 8 2 ) ( R L G C )

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