AIMC Topic: Computer Simulation

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Survival prediction model for right-censored data based on improved composite quantile regression neural network.

Mathematical biosciences and engineering : MBE May 20, 2022
With the development of the field of survival analysis, statistical inference of right-censored data is of great importance for the study of medical diagnosis. In this study, a right-censored data survival prediction model based on an improved compos...
Neural Networks, Computer Algorithms Computer Simulation Probability Survival Analysis
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Optical bone densitometry robust to variation of soft tissue using machine learning techniques: validation by Monte Carlo simulation.

Journal of biomedical optics May 1, 2022
SIGNIFICANCE: To achieve early detection of osteoporosis, a simple bone densitometry method using optics was proposed. However, individual differences in soft tissue structure and optical properties can cause errors in quantitative bone densitometry....
Humans Machine Learning Computer Simulation Osteoporosis Monte Carlo Method Densitometry
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Estimation of left ventricular parameters based on deep learning method.

Mathematical biosciences and engineering : MBE Apr 27, 2022
Estimating material properties of personalized human left ventricular (LV) modelling is a central problem in biomechanical studies. In this work we use deep learning (DL) method to evaluating the passive myocardial mechanical properties inversely. In...
Humans Computer Simulation Deep Learning Myocardium Heart Ventricles Diastole
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[Evaluation of brain injury caused by stick type blunt instruments based on convolutional neural network and finite element method].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Apr 25, 2022
The finite element method is a new method to study the mechanism of brain injury caused by blunt instruments. But it is not easy to be applied because of its technology barrier of time-consuming and strong professionalism. In this study, a rapid and ...
Humans Neural Networks, Computer Brain Computer Simulation Brain Injuries Finite Element Analysis
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Sliding-mode controller synthesis of robotic manipulator based on a new modified reaching law.

Mathematical biosciences and engineering : MBE Apr 22, 2022
In this study, an adaptive modified reaching law-based switch controller design was developed for robotic manipulator systems using the disturbance observer (DO) approach. Firstly, a standard DO is employed to estimate the unknown disturbances of the...
Computer Simulation Robotics Robotic Surgical Procedures Nonlinear Dynamics
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Enhanced performance of a reservoir computing system based on a dual-loop optoelectronic oscillator.

Applied optics Apr 20, 2022
Time-delayed reservoir computing (RC) is a brain inspired paradigm for processing temporal information, with simplification in the network's architecture using virtual nodes embedded in a temporal delay line. In this work, a novel, to the best of our...
Neural Networks, Computer Computer Simulation Semiconductors
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Desynchronous learning in a physics-driven learning network.

The Journal of chemical physics Apr 14, 2022
In a neuron network, synapses update individually using local information, allowing for entirely decentralized learning. In contrast, elements in an artificial neural network are typically updated simultaneously using a central processor. Here, we in...
Neural Networks, Computer Computer Simulation Learning Neurons Physics
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The Delta Robot-A long travel nano-positioning stage for scanning x-ray microscopy.

The Review of scientific instruments Apr 1, 2022
A new stage design concept, the Delta Robot, is presented, which is a parallel kinematic design for scanning x-ray microscopy applications. The stage employs three orthogonal voice coils, which actuate parallelogram flexures. The design has a 3 mm tr...
Computer Simulation Robotics Radiography Microscopy X-Rays
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Model-assisted deep learning of rare extreme events from partial observations.

Chaos (Woodbury, N.Y.) Apr 1, 2022
To predict rare extreme events using deep neural networks, one encounters the so-called small data problem because even long-term observations often contain few extreme events. Here, we investigate a model-assisted framework where the training data a...
Neural Networks, Computer Computer Simulation Reproducibility of Results Deep Learning
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Orthogonality of diffractive deep neural network.

Optics letters Apr 1, 2022
Some rules of the diffractive deep neural network (DNN) are discovered. They reveal that the inner product of any two optical fields in DNN is invariant and the DNN acts as a unitary transformation for optical fields. If the output intensities of the...
Neural Networks, Computer Computer Simulation
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