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The Standard Precipitation Index (SPI 12 and SPI 24) was forecasted using a traditional stochastic model (ARIMA) and compared to machine learning techniques such as artificial neural networks (ANNs), and support vector regression (SVR).
Compared to machine learning approaches this makes the results easily understandable; false positives can be pin-pointed to a particular grammar/dictionary and false negatives are readily corrected by adding the relevant nomenclature rule to a grammar or trivial name to a dictionary.
PathoLogic is known to perform well when compared to machine learning methods using the genomes of cellular organisms as input [ 21].
These two profiles (TP and SM) were used with a topography-driven smoking machine to investigate if replicating the true puffing topography results in differences in fine (>0.1 μm) and ultrafine (≤0.1 μm) particle size distributions and mainstream smoke emissions of selected volatile and semivolatile compounds compared to machine smoking using averaged, smoothed puff profiles.
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But, Ford adds, it is increasingly obvious that we are becoming less and less useful compared to machines.
Pre-planning is required as you need to put the bowl into the freezer between eight and 24 hours prior to making the ice cream, but the cost saving compared to machines with a built-in freezer element makes this worthwhile.
In classical paper-and-pencil assessments, the reading of handwritten student data is much more time consuming and interpretations are more error prone compared to machine-aided student answers.
Using wiper PCBN inserts reduces surface roughness compared to machining experiments with conventional inserts at increased feed rate.
For the same feed rate the machining force of GFRP laminates was observed to be very minimal, when compared to machining force of CFRP laminates.
This assumption could be due to the lower cost of labor compared to machines or the complexity of dual-resource constrained problems.
"If you read the questions and answers on Linqapp and see how people dig deep into them, it highlights how intricate languages are," says Ang. "Answers from people are still going to be the place to go to compared to machines, because they don't understand how complex languages are".
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com