AIMC Topic: Physical Phenomena
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Sensor-based particle mass prediction of lightweight packaging waste using machine learning algorithms.
Waste management (New York, N.Y.)
Oct 26, 2021
Sensor-based material flow characterization (SBMC) promises to improve the performance of future-generation sorting plants by enabling new applications like automatic quality monitoring or process control. Prerequisite for this is the derivation of m...
Wafer-Scale 2D Hafnium Diselenide Based Memristor Crossbar Array for Energy-Efficient Neural Network Hardware.
Advanced materials (Deerfield Beach, Fla.)
Sep 12, 2021
Memristor crossbar with programmable conductance could overcome the energy consumption and speed limitations of neural networks when executing core computing tasks in image processing. However, the implementation of crossbar array (CBA) based on ultr...
Nonlinear tensor train format for deep neural network compression.
Neural networks : the official journal of the International Neural Network Society
Sep 8, 2021
Deep neural network (DNN) compression has become a hot topic in the research of deep learning since the scale of modern DNNs turns into too huge to implement on practical resource constrained platforms such as embedded devices. Among variant compress...
The Impact of the Integrated Development of AI and Energy Industry on Regional Energy Industry: A Case of China.
International journal of environmental research and public health
Aug 25, 2021
With the advent of the Energy 4.0 era, the adoption of "Internet + artificial intelligence" systems will enable the transformation and upgrading of the traditional energy industry. This will alleviate the energy and environmental problems that China ...
Production of biofuels from biomass: Predicting the energy employing artificial intelligence modelling.
Bioresource technology
Jul 23, 2021
Bioenergy may be a major replacement of fossil fuels which can make the path easier for sustainable development and decrease the dependency on conventional sources of energy. The main concern with the bioenergy is the availability of feedstock, deali...
Remote Modular Electronics for Wireless Magnetic Devices.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Jul 10, 2021
Small-scale wireless magnetic robots and devices offer an effective solution to operations in hard-to-reach and high-risk enclosed places, such as inside the human body, nuclear plants, and vehicle infrastructure. In order to obtain functionalities b...
Physics-based protein structure refinement in the era of artificial intelligence.
Proteins
Jun 29, 2021
Protein structure refinement is the last step in protein structure prediction pipelines. Physics-based refinement via molecular dynamics (MD) simulations has made significant progress during recent years. During CASP14, we tested a new refinement pro...
Machine Learning of Analytical Electron Density in Large Molecules Through Message-Passing.
Journal of chemical information and modeling
May 19, 2021
Machine learning milestones in computational chemistry are overshadowed by their unaccountability and the overwhelming zoo of tools for each specific task. A promising path to tackle these problems is using machine learning to reproduce physical magn...
Event-triggered adaptive neural networks control for fractional-order nonstrict-feedback nonlinear systems with unmodeled dynamics and input saturation.
Neural networks : the official journal of the International Neural Network Society
May 18, 2021
The event-triggered adaptive neural networks control is investigated in this paper for a class of fractional-order systems (FOSs) with unmodeled dynamics and input saturation. Firstly, in order to obtain an auxiliary signal and then avoid the state v...
Improvement of image quality for pancreatic cancer using deep learning-generated virtual monochromatic images: Comparison with single-energy computed tomography.
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)
Apr 30, 2021
PURPOSE: To construct a deep convolutional neural network that generates virtual monochromatic images (VMIs) from single-energy computed tomography (SECT) images for improved pancreatic cancer imaging quality.
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