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Two different drilling system selection approaches were discussed based on a combination of the multi-attribute utility theory and the exhaustive search optimization, which are formulated as a non-causal and a causal approach.
We used a negative binomial regression model to compare the monthly pneumonic lung condemnation rates from the 3 sentinel surveillance system selection approaches for each animal class to the full dataset.
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In a real application, a non-causal system selection approach is not recommended as the best practice.
One follows a simple system selection approach where no formal consideration on the dependencies between the system components was considered (non-causal approach).
Notice that the configuration of the influence diagram for the non-causal system selection approach denotes no influences between the system's main components.
In this paper, we consider multiple-input multipleoutput (MIMO) systems where antenna elements are placed side by side in a limited-size linear array, and we examine the performance of some typical antenna selection approaches in such systems and under various scenarios of antenna spacing and mutual coupling.
The goal of the study was to compare abattoir selection approaches for a sentinel surveillance system based on provincially inspected abattoirs in Ontario.
This result shows that the causal approach yields a more systematic system selection - considering total drilling time variation.
Indeed, we feel that multi-model inference could be an appropriate alternative to overcome some of the limitations of classical selection approaches, especially when studying complex ecological systems.
However, should the purpose of the surveillance system be to measure the overall condemnation rates, the overestimation of all sentinel abattoir selection approaches would give inaccurate results.
Thus, the system selection and further developments were user-centered, based on user needs and on a participative approach.
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