AIMC Topic: Computer Simulation

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The Delta Robot-A long travel nano-positioning stage for scanning x-ray microscopy.

The Review of scientific instruments
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...

Model-assisted deep learning of rare extreme events from partial observations.

Chaos (Woodbury, N.Y.)
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...

Orthogonality of diffractive deep neural network.

Optics letters
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...

AutoSolvate: A toolkit for automating quantum chemistry design and discovery of solvated molecules.

The Journal of chemical physics
The availability of large, high-quality datasets is crucial for artificial intelligence design and discovery in chemistry. Despite the essential roles of solvents in chemistry, the rapid computational dataset generation of solution-phase molecular pr...

Learning spectral initialization for phase retrieval via deep neural networks.

Applied optics
Phase retrieval (PR) arises from the lack of phase information in the measures recorded by optical sensors. Phase masks that modulate the optical field and reduce ambiguities in the PR problem by producing redundancy in coded diffraction patterns (CD...

Neural-network-based method for improving measurement accuracy of four-quadrant detectors.

Applied optics
Due to the high accuracy and fast response, measurement systems based on four-quadrant detectors (4QDs) are widely used. There is a non-linear relationship between the output signal offset (OSO) of the 4QD and the actual spot position, resulting in l...

A deep learning framework for characterization of genotype data.

G3 (Bethesda, Md.)
Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for v...

Neural network-based adaptive synchronization for second-order nonlinear multiagent systems with unknown disturbance.

Chaos (Woodbury, N.Y.)
This paper handles the distributed adaptive synchronization problem for a class of unknown second-order nonlinear multiagent systems subject to external disturbance. It is supposed to be an unknown one for the underlying external disorder. First, the...

[Structural design and performance analysis of an auxiliary dining robot].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
An auxiliary dining robot is designed in this paper, which implements the humanoid feeding function with theory of inventive problem solving (TRIZ) theory and aims at the demand of special auxiliary nursing equipment. Firstly, this robot simulated th...

SuperMICE: An Ensemble Machine Learning Approach to Multiple Imputation by Chained Equations.

American journal of epidemiology
Researchers often face the problem of how to address missing data. Multiple imputation is a popular approach, with multiple imputation by chained equations (MICE) being among the most common and flexible methods for execution. MICE iteratively fits a...