AIMC Topic: Temperature

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PM2.5 concentration modeling and prediction by using temperature-based deep belief network.

Neural networks : the official journal of the International Neural Network Society Nov 5, 2020
Air quality prediction is a global hot issue, and PM is an important factor affecting air quality. Due to complicated causes of formation, PM prediction is a thorny and challenging task. In this paper, a novel deep learning model named temperature-ba...
Particulate Matter Environmental Monitoring Air Pollutants Humans Neural Networks, Computer Forecasting Temperature
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Application of deep neural techniques in predictive modelling for the estimation of Escherichia coli growth rate.

Journal of applied microbiology Nov 3, 2020
AIMS: To develop a predictive model for Escherichia coli using deep neural networks.
Neural Networks, Computer Escherichia coli Models, Biological Food-Processing Industry Temperature Reproducibility of Results
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Predicting dairy cattle heat stress using machine learning techniques.

Journal of dairy science Oct 31, 2020
The objectives of the study were to use a heat stress scoring system to evaluate the severity of heat stress on dairy cows using different heat abatement techniques. The scoring system ranged from 1 to 4, where 1 = no heat stress; 2 = mild heat stres...
Respiratory Rate Hot Temperature Dairying Lactation Milk Heat Stress Disorders Body Temperature Cattle Diseases Bayes Theorem Animals Cattle Female Machine Learning Temperature
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A Machine Learning Protocol for Predicting Protein Infrared Spectra.

Journal of the American Chemical Society Oct 30, 2020
Infrared (IR) absorption provides important chemical fingerprints of biomolecules. Protein secondary structure determination from IR spectra is tedious since its theoretical interpretation requires repeated expensive quantum-mechanical calculations i...
Machine Learning Proteins Amides Quantum Theory Temperature Peptides Protein Structure, Secondary Protein Folding Ubiquitin Spectrophotometry, Infrared
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Machine Learning-Based Activity Pattern Classification Using Personal PM Exposure Information.

International journal of environmental research and public health Sep 9, 2020
The activity pattern is a significant factor in identifying hotspots of personal exposure to air pollutants, such as PM. However, the recording process of an activity pattern can be annoying to study participants, because they are often asked to brin...
Humans Machine Learning Particulate Matter Temperature Environmental Exposure Environmental Monitoring Child Air Pollutants
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A Time Series Data Filling Method Based on LSTM-Taking the Stem Moisture as an Example.

Sensors (Basel, Switzerland) Sep 5, 2020
In order to solve the problem of data loss in sensor data collection, this paper took the stem moisture data of plants as the object, and compared the filling value of missing data in the same data segment with different data filling methods to verif...
Neural Networks, Computer Temperature
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Human thermal sensation over a mountainous area, revealed by the application of ANNs: the case of Ainos Mt., Kefalonia Island, Greece.

International journal of biometeorology Aug 28, 2020
Mt. Ainos in Kefalonia Island, Greece, hosts a large variety of plant species, some of them endemic to the region. Because of its rich biodiversity, a large portion of the mountain area is designated as National Park and is protected from human activ...
Greece Islands Temperature Thermosensing Humans Neural Networks, Computer
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Applications of machine learning in behavioral ecology: Quantifying avian incubation behavior and nest conditions in relation to environmental temperature.

PloS one Aug 28, 2020
In the age of machine learning, building programs that take advantage of the speed and specificity of algorithm development can greatly aid efforts to quantify and interpret changes in animal behavior in response to abiotic environmental factors, lik...
Birds Temperature Machine Learning Ecological and Environmental Phenomena Nesting Behavior Animals Software
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Biosynthetic self-healing materials for soft machines.

Nature materials Jul 27, 2020
Self-healing materials are indispensable for soft actuators and robots that operate in dynamic and real-world environments, as these machines are vulnerable to mechanical damage. However, current self-healing materials have shortcomings that limit th...
Kinetics Biocompatible Materials Robotics Equipment Design Mechanical Phenomena Temperature
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Improving Enzyme Optimum Temperature Prediction with Resampling Strategies and Ensemble Learning.

Journal of chemical information and modeling Jul 22, 2020
Accurate prediction of the optimal catalytic temperature () of enzymes is vital in biotechnology, as enzymes with high values are desired for enhanced reaction rates. Recently, a machine learning method (temperature optima for microorganisms and enz...
Temperature Machine Learning
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