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The first method uses computer image analysis of satellite photos and data to measure the spread and thickness of oil on the ocean surface.
The Artificial Neural Network (ANN) method uses computer algorithms (machine learning), applying non-linear statistics to pattern recognition.
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Based on psychological aspects, the method uses computers to analyse and measure the pertinent attributes.
Furthermore, we describe control mark detection method using computer vision algorithms, and its localization from single image.
Previous methods to calculate the correction angle are inconvenient and complicated, whereas the method using computer simulations may be very effective and much simpler than existing methods.
Reliability of the new estimator is compared with that from the heterozygote-excess method using computer simulation.
The bias and confidence interval of the new estimator are compared with those from a published method, i.e. the heterozygote-excess method, using computer simulation.
We evaluate the performance of our method using computer simulation, and illustrate its utility by analyzing the human sas gene pair with the longest overlapping region.
The lead clinician randomised participants to either the best practice (control) group or the MoleMate (intervention) group on the basis of a block randomisation method, using computer generated, randomly permuted blocks of size 2, 4, and 6, established by the trial statistician (ATP).
We stratified randomisation by site and maintained balance between groups within each stratum using a minimisation method using computer-generated random numbers to give an equal chance of allocation to each group when groups within the stratum were balanced and an increased chance (0.667) of allocation to the smaller group when there was an imbalance within the stratum.
Advanced magnetic resonance imaging (MRI -based VOI definition MRI -basede computer VOIion techniques for the segmentation of the definitionructures.
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