Noise-injected analog Ising machines enable ultrafast statistical sampling and machine learning

Noise-induced Boltzmann sampling with analog Ising machines Boltzmann sampling is the task of approximating the Boltzmann distribution function for an ensemble of N systems $$P({\{\sigma \}}_{i})=\frac{{e}^{-E({\{\sigma \}}_{i})/T}}{{\sum }_{q}{e}^{-E({\{\sigma \}}_{q})/T}},$$ (1) where P({σ}i) is the probability of measuring a state {σ}i = {σ1, σ2, …, σN} with the corresponding energy E({σ}i) at a given temperature T. Here, we… Continue reading Noise-injected analog Ising machines enable ultrafast statistical sampling and machine learning

Iterative image segmentation of plant roots for high-throughput phenotyping

In this section we outline our approach to the problem of segmenting thin and highly branched root structures. We designed a tool for fast and consistent annotation of root images to produce ground truth binary masks for use in training and evaluation of segmentation algorithms. We also designed a neural network architecture which is particularly… Continue reading Iterative image segmentation of plant roots for high-throughput phenotyping

The distribution of initial estimates moderates the effect of social influence on the wisdom of the crowd

Galton, F. Vox populi. Nature 75, 450–451 (1907). ADS  Article  Google Scholar  Surowiecki, J. The Wisdom of Crowds (Knopf Doubleday Publishing Group, 2005). Wolfers, J. & Zitzewitz, E. Prediction markets. J. Econ. Perspect. 18, 107–126 (2004). Article  Google Scholar  Barneron, M., Allalouf, A. & Yaniv, I. Rate it again: Using the wisdom of many to… Continue reading The distribution of initial estimates moderates the effect of social influence on the wisdom of the crowd

Modelling brain dynamics by Boolean networks

Let us investigate whether there is any relationship among the emerged circuits for this simulation. The easiest and quickest way is to adopt the intersections between the areas of the emerged circuits. In Table 6 we show the intersection between these 10 circuits. Table 6 Diagram of representation of the intersection among the emerged circuits… Continue reading Modelling brain dynamics by Boolean networks

Large waves and navigation hazards of the Eastern Mediterranean Sea

This section is structured as follows. First, we discuss the metocean characteristics of the sea states generated by the two observed storms as they passed through the Eastern Mediterranean. Relevant wave parameters and statistical models are defined in the “Methods” section. Then, we make prediction on the extreme waves during the two storms. To do… Continue reading Large waves and navigation hazards of the Eastern Mediterranean Sea

High-quality restoration image encryption using DCT frequency-domain compression coding and chaos

DCT DCT is a kind of orthogonal transformation32. Compared with fast Fourier transform (FFT) and Discrete wavelet transform (DWT), DCT can save arithmetic power and maintain good performance7. Let \(\{X_{m}|{m=0,1,\ldots ,N-1}\}\) be a signal sequence with length N, and 1D discrete chord transform (1D-DCT) is defined as: $$\begin{aligned} Y(u)=C(u)\sqrt{\frac{2}{N}}\sum _{m=0}^{N-1}X(m){\mathrm{cos}} \frac{(2m+1)u\pi }{2N},u=1,2,\ldots ,N-1 \end{aligned}$$ (1)… Continue reading High-quality restoration image encryption using DCT frequency-domain compression coding and chaos

Physically constrained generative adversarial networks for improving precipitation fields from Earth system models

Palmer, T. & Stevens, B. The scientific challenge of understanding and estimating climate change. Proc. Natl Acad. Sci. USA. 116, 24390–24395 (2019). Article  Google Scholar  Wilcox, E. M. & Donner, L. J. The frequency of extreme rain events in satellite rain-rate estimates and an atmospheric general circulation model. J. Clim. 20, 53–69 (2007). Article  Google… Continue reading Physically constrained generative adversarial networks for improving precipitation fields from Earth system models

Demand-driven design of bicycle infrastructure networks for improved urban bikeability

Cyclist route choice model The benefit of bike paths fundamentally depends on their usage and in turn on the routes of cyclists. We map cyclists’ route choices to a shortest-path problem on a preference graph G = (V, E) with N = ∣V∣ number of nodes (intersections) and M = ∣E∣ number of edges (street segments). We derive the preference graph G… Continue reading Demand-driven design of bicycle infrastructure networks for improved urban bikeability

Designing efficient urban bike path networks that meet the needs of cyclists

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This is a summary of: Steinacker, C. et al. Demand-driven design of bicycle infrastructure networks for improved urban bikeability. Nat. Comput. Sci. https://doi.org/10.1038/s43588-022-00318-w (2022). Continue Reading News Source: https://www.nature.com/articles/s43588-022-00324-y