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For our purposes, a plan contains a series of steps or milestones for guiding achievement accompanied by a schedule and resource allocations How are plans different from processes and activities Enterprise processes and their component activities are recurring capabilities that may be engaged or applied to achieving plans Plans are intended to address the production of results such as problems solved, needs satis ed, opportunities exploited, and products produced all with associated measures and metrics Plans include attributes such as volume, rate, frequency, milestones, labor allocations, burn rates, and other resource allocations and utilizations resulting in costs, and accounting for assets, and value production Data are input to plans as well as input to processes Data are outputs of plans and processes Data are evidence of accomplishment [A2] De ne Enterprise Controls We prefer calling enterprise controls the enterprise leadership and integration architecture It accounts for management processes and their associated controls that permeate the organization as controls on subordinate processes To a large extent, controls shape the brand of management As stated before, controls on government enterprise contain all of the laws and regulations as well as policies and guidances that may appear as memos and other communiqu s such as visionary plans and programs e One de nition of program is a system of projects or services intended to meet a public need That is a complex idea First, the existence of a program represents management s decision to commit considerable resources to produce results from an effort of considerable scope and scale Therefore identifying a program as a part of a plan might constitute a statement of leadership intention, commitment, and control as it de nes budget allocation and time constraints A strategy may be executed as a program whereby to accomplish it requires special resource commitment and management focus Smart data strategy would manifest programmatically by the following: 1 Executive policy statement emphasizing the importance of operational entities having a data strategy that contributes explicitly to the enterprise data strategy as de ned in the policy 2 Using smart data strategy as a catalyst for change and improvement as an enterprise initiative 3 Adding and implementing smart data strategy enablement including adding new skill sets and new technologies [A3] Identify and De ne Enterprise Inputs Enterprise inputs include accounting for all resources, capital, and materials that are consumed and transformed by the enterprise into intended outcomes Under the smart data strategy approach, all resources would be accounted for by tracking their use and transformation through enterprise processes, concluding with classi cation into assets, results, cost, waste, and noise.

1 (ya )4

0% 10% less 15% less 27% less 30% less 35% less 386% less $0 $1240 $3015 $15099 $21549 $38819 $60754

The above probabilities use a di erent local density calculation, where an additional constraint is added: (ya ) = max{0, n1 2 N 0

yb NnN nN (i) (1

Table B(1) BIWEEKLY PAYROLL PERIOD (Amount for each allowance claimed is $11731)

ISO 10303 PLCS BPM/BPEL Metadata management Component-based architecture RDF/OWL Semantic mediation XML schema

d(ya yb ) )}

$0 $102 $329 $1,158 $2,535 $5,585 $12,063

d(ya ,yb ) )

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(1758) Heterogeneous Ants: The Lumer Faieta clustering algorithm uses homogeneous ants That is, all ants have the same behavior as governed by static control parameters, nN and Using static control parameters introduces the problem of nding optimal values for these parameters Since the best values for these parameters depend on the data set being clustered, the parameters should be optimized for each new data set Heterogeneous ants address this problem by having di erent values for the control parameters for each ant Monmarch et al e [601] randomly selected a value for each control parameter for each ant within de ned ranges New values can be selected for each iteration of the algorithm or can remain static Handl et al [344] used heterogeneous ants with dynamically changing values for nN and Ants start with small values of nN , which gradually increase over time This approach saves on computational e ort during the rst iterations

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