Sentence examples for implementation for handling from inspiring English sources

The naive Bayes classifier that yields optimal performance in many statistical applications is used for identification due to the simplicity of its implementation for handling huge size face database.

Coelho et al. (2008) performed an empirical study considering the fault-proneness of aspect-oriented implementations for handling exceptions.

The Fuzzy Control Medium Access (FCMA) [49] implements acquisition, fuzzy logic control, and implementation phases for handling the non-real time data, normal real-time data, abnormal data, and emergency data of a patient body.

This will require the development and implementation of systems for handling very large image datasets, and for making them available to the user community for visualisation and analysis.

Implementation of methods for handling missing covariate data in NONMEM: The population model used for simulations and estimations:where MALE is the sex covariate (1 if male and 0 if female), CL is the drug clearance and Y is the response variable, i.e. the log-transformed steady-state concentrations.

First, for each exception raised by a service, the same exception is delivered to all composition's participants, decreasing the flexibility for the implementation of handling actions.

We discuss the actual implementation of the system for handling Natura 2000 sites in the Catalan and Spanish contexts.

Green awareness and implementation of e-waste management rules prompted them to think about implementing RL system for handling product returns and EOL computers.

Given the limitations of the current implementation, our software is suitable for handling problems involving tens of variables and parameters but possibly not suited for problem dimensionality on the order of hundreds or higher.

This paper introduces a set of parallel implementations of a hybrid algorithm for handling descriptors and a detailed performance analysis on four real Markovian models.

Multi-netclust is not a new clustering method but an optimized implementation of existing graph algorithms suitable for handling large networks of > 10 nodes and 10 edges.