AIMC Topic: Electricity

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Artificial Electrical Morris-Lecar Neuron.

IEEE transactions on neural networks and learning systems Oct 13, 2014
In this paper, an experimental electronic neuron based on a complete Morris-Lecar model is presented, which is able to become an experimental unit tool to study collective association of coupled neurons. The circuit design is given according to the i...
Neurons Electronics Nerve Net Electricity Neural Networks, Computer Models, Neurological Humans
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Prediction of electrical load demand using combined LHS with ANFIS.

PloS one Jan 1, 2025
Enhancement prediction of load demand is crucial for effective energy management and resource allocation in modern power systems and especially in medical segment. Proposed method leverages strengths of ANFIS in learning complex nonlinear relationshi...
Machine Learning Algorithms Humans Neural Networks, Computer Electricity Electric Power Supplies Fuzzy Logic Monte Carlo Method
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Emulating biological synaptic characteristics of HfOx/AlN-based 3D vertical resistive memory for neuromorphic systems.

The Journal of chemical physics Apr 14, 2024
Here, we demonstrate double-layer 3D vertical resistive random-access memory with a hole-type structure embedding Pt/HfOx/AlN/TiN memory cells, conduct analog resistive switching, and examine the potential of memristors for use in neuromorphic system...
Neural Networks, Computer Electricity
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[Research and application of photovoltaic cell online monitoring system for animal robot stimulator].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Oct 25, 2022
Power supply plays a key role in ensuring animal robots to obtain effective stimulation. To extending the stimulating time, there is a need to apply photovoltaic cells and monitor their parameter variations, which can help operators to obtain the opt...
Electricity Electric Power Supplies User-Computer Interface Robotics Humans Animals
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Molecular dipole moment learning via rotationally equivariant derivative kernels in molecular-orbital-based machine learning.

The Journal of chemical physics Sep 14, 2022
This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree-Fock computations. A MOB pairwise decomposition ...
Machine Learning Normal Distribution Electricity Water Electrons
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3D printable and fringe electric field adhesion enabled variable stiffness artificial muscles for semi-active vibration attenuation.

Soft matter Jul 21, 2021
Soft robots are able to generate large and compliant deformation in an unconstructed environment, but their operation capability is limited by low stiffness. Thus, developing the function of variable stiffness while preserving its compliance is a cha...
Vibration Electricity Muscles Robotics
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From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

Proceedings of the National Academy of Sciences of the United States of America Jun 29, 2021
The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational dat...
Vehicle Emissions Electricity Transportation Air Pollution Particulate Matter Air Pollutants Machine Learning COVID-19 Algorithms Models, Theoretical Humans
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Extracting electricity with exosuit braking.

Science (New York, N.Y.) May 28, 2021
Biomechanical Phenomena Robotics Exoskeleton Device Walking Electricity
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[Intelligent fault diagnosis of medical equipment based on long short term memory network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Apr 25, 2021
In order to solve the current problems in medical equipment maintenance, this study proposed an intelligent fault diagnosis method for medical equipment based on long short term memory network(LSTM). Firstly, in the case of no circuit drawings and un...
Algorithms Electricity Neural Networks, Computer
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Micrometer-sized electrically programmable shape-memory actuators for low-power microrobotics.

Science robotics Mar 17, 2021
Shape-memory actuators allow machines ranging from robots to medical implants to hold their form without continuous power, a feature especially advantageous for situations where these devices are untethered and power is limited. Although previous wor...
Smart Materials Electricity Robotics Electrochemical Techniques Humans Oxidation-Reduction Microtechnology Mechanical Phenomena Equipment Design Platinum
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