BACKGROUND Habitat selection and its adaptive outcomes are crucial features for animal life-history strategies. Nevertheless, congruence between habitat preferences and breeding success has been rarely demonstrated, which may result from the single-scale evaluation of animal choices. As habitat selection is a complex multi-scale process in many groups of animal species, investigating adaptivene...

Dust evolution simulation provides an important way to analyze the impact of dust on the environment. Since wind speed plays a key role in dust evolution, multi-scale simulation is applied to simulate the wind speed in order to improve the accuracy of wind speed simulation and reduce the amount of calculation. Through k-means clustering, the virtual campus can be divided by grids with different...

Even though convolutional neural networks (CNN) has achieved near-human performance in various computer vision tasks, its ability to tolerate scale variations is limited. The popular practise is making the model bigger first, and then train it with data augmentation using extensive scale-jittering. In this paper, we propose a scaleinvariant convolutional neural network (SiCNN), a model designed...

Decision-makers in organizations and other hierarchical systems interact within and across multiple organizational levels and take interdependent actions over time. The challenge is to identify incentive mechanisms that align agents’ interests and to provide these agents with guidance for their decision processes. To this end, we developed a multiscale decision-making model that combines game t...

Biological processes involve a variety of spatial and temporal scales. A holistic understanding of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript we review mathematical modelling approaches used to describe the individual spatial scales and how they are integrated into holistic models. We discuss the ...

In this article we describe a Bayesian model for integration of multi-scale image data. The approach is based on the concept of a reference resolution. Data at this and lower resolutions are connected to the reference resolution through a fully specified statistical model. Algorithms for parameter estimation and classification based on the multi-scale model are proposed, and results and compari...

We propose scale-free Identifier Network(sfIN), a novel model for event identification in documents. In general, sfIN first encodes a document into multi-scale memory stacks, then extracts special events via conducting multi-scale actions, which can be considered as a special type of sequence labelling. The design of large scale actions makes it more efficient processing a long document. The wh...