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Diffusion

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Double graph correlation encryption based on hyperchaos.

PloS one
Preventing unauthorized access to sensitive data has always been one of the main concerns in the field of information security. Accordingly, various solutions have been proposed to meet this requirement, among which encryption can be considered as on...

Robotic Surgery in Urology: History from PROBOT to HUGO.

Sensors (Basel, Switzerland)
The advent of robotic surgical systems had a significant impact on every surgical area, especially urology, gynecology, and general and cardiac surgery. The aim of this article is to delineate robotic surgery, particularly focusing on its historical ...

Adv-BDPM: Adversarial attack based on Boundary Diffusion Probability Model.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks have become increasingly significant in our daily lives due to their remarkable performance. The issue of adversarial examples, which are responsible for the vulnerability problem of deep neural networks, has attracted the attent...

Design of New Inorganic Crystals with the Desired Composition Using Deep Learning.

Journal of chemical information and modeling
New solid-state materials have been discovered using various approaches from atom substitution in density functional theory (DFT) to generative models in machine learning. Recently, generative models have shown promising performance in finding new ma...

Inferring pointwise diffusion properties of single trajectories with deep learning.

Biophysical journal
To characterize the mechanisms governing the diffusion of particles in biological scenarios, it is essential to accurately determine their diffusive properties. To do so, we propose a machine-learning method to characterize diffusion processes with t...

Event-triggered impulsive cluster synchronization of coupled reaction-diffusion neural networks and its application to image encryption.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the cluster synchronization of coupled neural networks with reaction-diffusion terms. With the help of impulsive control strategies, some cluster synchronization criteria are proposed by an appropriate event-triggered mechanis...

Preassigned-time synchronization for complex-valued memristive neural networks with reaction-diffusion terms and Markov parameters.

Neural networks : the official journal of the International Neural Network Society
This study addresses the preassigned-time synchronization for complex-valued memristive neural networks with reaction-diffusion terms and Markov parameters. Employing a preassigned-time stable control strategy, two distinct controllers with varying p...

De novo design of high-affinity binders of bioactive helical peptides.

Nature
Many peptide hormones form an α-helix on binding their receptors, and sensitive methods for their detection could contribute to better clinical management of disease. De novo protein design can now generate binders with high affinity and specificity ...

Memristor-induced hyperchaos, multiscroll and extreme multistability in fractional-order HNN: Image encryption and FPGA implementation.

Neural networks : the official journal of the International Neural Network Society
Fractional-order differentiation (FOD) can record information from the past, present, and future. Compared with integer-order systems, FOD systems have higher complexity and more accurate ability to describe the real world. In this paper, two types o...

SPIN-CGNN: Improved fixed backbone protein design with contact map-based graph construction and contact graph neural network.

PLoS computational biology
Recent advances in deep learning have significantly improved the ability to infer protein sequences directly from protein structures for the fix-backbone design. The methods have evolved from the early use of multi-layer perceptrons to convolutional ...