AIMC Topic: Gases

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Machine Learning Directed Optimization of Classical Molecular Modeling Force Fields.

Journal of chemical information and modeling Aug 17, 2021
Accurate force fields are necessary for predictive molecular simulations. However, developing force fields that accurately reproduce experimental properties is challenging. Here, we present a machine learning directed, multiobjective optimization wor...
Models, Molecular Gases Thermodynamics Machine Learning Prospective Studies
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Performance for rotor system of hybrid electromagnetic bearing and elastic foil gas bearing with dynamic characteristics analysis under deep learning.

PloS one Mar 15, 2021
The bearing-rotor system is prone to faults during operation, so it is necessary to analyze the dynamic characteristics of the bearing-rotor system to discuss the optimal structure of the convolutional neural network (CNN) in system fault detection a...
Deep Learning Pressure Magnetics Gases
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Bubbly flow prediction with randomized neural cells artificial learning and fuzzy systems based on k-ε turbulence and Eulerian model data set.

Scientific reports Aug 14, 2020
Computing gas and liquid interactions based on interfacial force models require a proper turbulence model that accurately resolve the turbulent scales such as turbulence kinetic energy and turbulence dissipation rate with cheap computational resource...
Gases Machine Learning Neural Networks, Computer Models, Theoretical Hydrodynamics Algorithms Fuzzy Logic Artificial Intelligence Computer Simulation Datasets as Topic
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Sensor-Array Optimization Based on Time-Series Data Analytics for Sanitation-Related Malodor Detection.

IEEE transactions on biomedical circuits and systems Jun 12, 2020
There is an unmet need for a low-cost instrumented technology for detecting sanitation-related malodor as an alert for maintenance around shared toilets and emerging technologies for onsite waste treatment. In this article, our approach to an electro...
Humans Neural Networks, Computer Equipment Design Odorants Urine Machine Learning Algorithms Feces Toilet Facilities Gases Electronic Nose
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Machine Learning and Bioinformatics Models to Identify Pathways that Mediate Influences of Welding Fumes on Cancer Progression.

Scientific reports Feb 17, 2020
Welding generates and releases fumes that are hazardous to human health. Welding fumes (WFs) are a complex mix of metallic oxides, fluorides and silicates that can cause or exacerbate health problems in exposed individuals. In particular, WF inhalati...
Welding Gases Air Pollutants, Occupational Neoplasms Computational Biology Gene Expression Regulation, Neoplastic Neoplasm Proteins Metabolic Networks and Pathways Inhalation Exposure Humans Machine Learning
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Machine Vision Methods, Natural Language Processing, and Machine Learning Algorithms for Automated Dispersion Plot Analysis and Chemical Identification from Complex Mixtures.

Analytical chemistry Jul 29, 2019
Gas-phase trace chemical detection techniques such as ion mobility spectrometry (IMS) and differential mobility spectrometry (DMS) can be used in many settings, such as evaluating the health condition of patients or detecting explosives at airports. ...
Methyl n-Butyl Ketone Gases Complex Mixtures Image Processing, Computer-Assisted Humans Acetates Support Vector Machine Machine Learning Spectrum Analysis Natural Language Processing Software Butanones
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Automatic gas detection in prostate cancer patients during image-guided radiation therapy using a deep convolutional neural network.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Jun 21, 2019
PURPOSE: The detection of intestinal/rectal gas is very important during image-guided radiation therapy (IGRT) of prostate cancer patients because intestinal/rectal gas increases the inter- and intra-fractional prostate motion. We propose a deep conv...
Radiotherapy, Image-Guided Tomography, X-Ray Computed Prostatic Neoplasms Male Automation Image Processing, Computer-Assisted Deep Learning Gases Intestines Humans
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Performance assessment of gas-phase toluene removal in one- and two-liquid phase biotrickling filters using artificial neural networks.

Chemosphere Jun 8, 2019
The main aim of this work is to study gas-phase toluene removal in one- and two-liquid phase biotrickling filters (O/TLP-BTF) and model the BTF performance using artificial neural networks (ANNs). The TLP-BTF was operated for 60 d in the presence of ...
Neural Networks, Computer Gases Air Pollutants Silicone Oils Kinetics Toluene Filtration
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Investigation of a rapid infrared heating assisted mineralization of soybean matrices for trace element analysis.

Food chemistry Dec 19, 2018
A fast sample preparation procedure based on use of infrared (IR) assisted heating for mineralization of soybean derived samples has been developed for their subsequent multielement analysis by inductively coupled plasma optical emission spectrometry...
Heating Gases Infrared Rays Trace Elements Limit of Detection Metals Glycine max Food Analysis Spectrophotometry, Atomic Phosphorus
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Improving the environmental impact of palm kernel shell through maximizing its production of hydrogen and syngas using advanced artificial intelligence.

The Science of the total environment Dec 19, 2018
Fossil fuel depletion and the environmental concerns have been under discussion for energy production for many years and finding new and renewable energy sources became a must. Biomass is considered as a net zero CO energy source. Gasification of bio...
Gases Arecaceae Hydrogen Fuzzy Logic Biofuels Pyrolysis Conservation of Energy Resources Nuts
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