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Physical Phenomena

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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
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...

Modeling, learning, perception, and control methods for deformable object manipulation.

Science robotics
Perceiving and handling deformable objects is an integral part of everyday life for humans. Automating tasks such as food handling, garment sorting, or assistive dressing requires open problems of modeling, perceiving, planning, and control to be sol...

Machine Learning of Analytical Electron Density in Large Molecules Through Message-Passing.

Journal of chemical information and modeling
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...

Physics-based protein structure refinement in the era of artificial intelligence.

Proteins
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...

Production of biofuels from biomass: Predicting the energy employing artificial intelligence modelling.

Bioresource technology
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)
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...

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
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 ...

Nonlinear tensor train format for deep neural network compression.

Neural networks : the official journal of the International Neural Network Society
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...

Wafer-Scale 2D Hafnium Diselenide Based Memristor Crossbar Array for Energy-Efficient Neural Network Hardware.

Advanced materials (Deerfield Beach, Fla.)
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...

A Novel Energy Compensation Scheme for Quality Enhancement in Time-Delayed Teleoperation With Multi-DoF Haptic Data Reduction and Communication.

IEEE transactions on haptics
Efficient and low-delay exchange of hapticinformation plays a key role for the design of high-fidelity teleoperation systems that operate over real-world communication networks. In the presence of communication unreliabilities such as delay and packe...