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Solid modeling procedures based on validated techniques are expected to provide valuable insights into the molecular mechanisms of nanoparticle-cell/tissue interactions and sound predictions of novel properties and applications.
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The objective of this paper is to present a modeling procedure, based on the use of statistical methods, to develop predictive models for Information Technology (IT) capacity planning.
Therefore, this paper firstly introduces a modeling procedure based on the static characteristics of systems.
This paper presents a methodology for modeling repetitive construction projects by introducing a modeling procedure based on the system model simulator nexus, with the aim of developing an intelligent tool to facilitate decision-making in the construction implementation phase.
The ADBQUICKEST scheme is a new TVD version of the QUICKEST [B.P. Leonard, A stable and accurate convective modeling procedure based on quadratic upstream interpolation, Computer Methods in Applied Mechanics and Engineering 19 (1979 59 98]] for solving nonlinear balance laws.
The performance of this modeling procedure based on (a combination of) the three standard methods has been evaluated by two previous studies in the same study area.
It is worth mentioning that in this research, calculations and modeling procedures were based on the first cycle of Bushehr's VVER-1000 reactor to study the feasibility of the proposed solution.
This SFR model is a simplified equivalent model, and its modeling procedure is based on the generator parameters.
The modeling procedure is based only on physical principles and geometrical considerations with no adjustable parameters in order to reconcile the theoretical work with the experimental data of the literature.
The modeling procedure is based on the concept of time-varying filtering.
Thus, automated and standardized data processing procedures, based on clearly defined criteria, such as statistical parameters and thresholds, are a prerequisite and highly desirable to guarantee the reproducibility and traceability of modeling results.
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