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International audience ; The paper overview one of the projects at the middle 80-th, supported by USSR government and oriented on breakthrough in hardware/software development. Several academic groups with industrial companies fulfilled a lot of investigations, built prototypes of perspective computers and intellectual programs. Author, as one of participants and headers of START project, analyses some principles of the project organizing structure. Although most brilliant results of START project were not used by industry because of economic and political crisis in Soviet Union, the impact of enthusiastic work and generating new ideas, was great for all major developers. Several opinions of participants are presented in conclusion.

The geometric characteristics of dust clouds provide important information on the physical processes that structure such clouds. One of such characteristics is the 2D fractal dimension D of a cloud projected on to the sky plane. In previous studies, which were mostly based on infrared (IR) data, the fractal dimension of individual clouds was found to be in a range from 1.1 to 1.7 with a preferred value of 1.2-1.4. In this work, we use data from Stripe82 of the Sloan Digital Sky Survey to measure the fractal dimension of the cirrus clouds. This is done here for the first time for optical data with significantly better resolution as compared to IR data. To determine the fractal dimension, the perimeter-area method is employed. We also consider IR (IRAS and Herschel) counterparts of the corresponding optical fields to compare the results between the optical and IR. We find that the averaged fractal dimension across all clouds in the optical is $\langle D \rangle =1.69{+0.05} {-0.05}$ which is significantly larger than the fractal dimension of its IR counterparts $\langle D\rangle =1.38{+0.07} {-0.06}$. We examine several reasons for this discrepancy (choice of masking and minimal contour level, image and angular resolution, etc.) and find that for approximately half of our fields the different angular resolution (point spread function) of the optical and IR data can explain the difference between the corresponding fractal dimensions. For the other half of the fields, the fractal dimensions of the IR and visual data remain inconsistent, which can be associated with physical properties of the clouds, but further physical simulations are required to prove it. © 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. ; We acknowledge financial support from the Russian Science Foundation (grant no. 20-72-10052). Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High Performance Computing at the University of Utah. The SDSS website is www.sdss.org. ; With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709. ; Peer reviewed