On joint application of atomic force microscopy and light scattering data for determination of growth rate for fractal solid state surface height

This work was supported by RFBR, grant N 18-08-01356-a

Deep neural networks performance optimization in image recognition

In this paper, we consider the problem of insufficient runtime and memory-space complexities of contemporary deep convolutional neural networks in the problem of image recognition. A survey of recent compression methods and efficient neural networks architectures is provided. The experimental study is focused on the visual emotion recognition problem. We compare the computational speed and memory consumption during the training and the inference stages of such methods as the weights matrix decomposition, binarization and hashing in the visual emotion recognition problem. It is experimentally shown that the most efficient recognition is achieved with the full network binarization and matrices decomposition.The article was prepared within the framework of the Academic Fund Program at the National Research University Higher School of Economics (HSE) in 2017 (grant №17-05-0007) and by the Russian Academic Excellence Project "5-100". A.V. Savchenko is supported by Russian Federation President grant no. МД-306.2017.9

On exact solution of the Kardar-Parisi-Zhang equation with determinate spatially-inhomogeneous source

This work was supported by RFBR, grant N 18-08-01356-a

SPECTRAL ANALYSIS OF ENERGY DISTRIBUTION AT TSUNAMI WAVE PROPAGATION IN OKHOTSK SEA BASIN

The presence of residual subduction zone under Kuril island arc makes a region of Kuril ridge islands be potential seismic-danger since underwater earthquakes in subduction zone with magnitude М > 6 are usually tsunamigenic. Potential strong earthquakes near the Kuril-Kamchatka trench passes along Kuril island, and tsunami generated by them carry a greater risk while passing through Bussol and Krusenstern straits for all Okhotsk seashore including the Sakhalin coast where now taking place a rising of infrastructure development connected with development an oil and gas industry. In the history, a few occasions of tsunami generation near the Sakhalin coast, caused by earthquakes in Kuril ridge region had been recorded (see, e.g. [1]). Such occasion taken place while strongest earthquake occurs recently near the Simushir island (15 November 2006). This earthquake and tsunami were predicted half of year before the event: while marine expedition clarified structure and size of possible undersea source in the area of seismic gap in Middle Kuril region. Then, the numericalsimulation of tsunami generation and propagation was performed using keyboard model of an earthquake. Since not all seismic gap area was activated, it’s interesting to perform a numerical modeling of potential catastrophic earthquake and tsunami in residual seismic gap of Middle Kuril and compare results with similar scenario of earthquake and tsunami for hypothetical source placed in inactive part of seismic gap. In this paper, such modeling was performed based on keyboard model of tsunamigenic earthquakes [2]. Calculation was performed using nonlinear shallow water equations and considering bottom dissipation. Spectral analysis of tsunami wave field in this model gives new possibilities for determination of energy characteristics of tsunami in the whole modeling area