July 30, Daily science and technology trend

  • 2020-07-30
  • 115

1. The products of the winner of this year's Startup Village competition, BioSmart Quasar facial identification terminal, BioSmart PV-WM palm vein reader and BioSmart PV-WTC terminal have successfully passed a series of rigorous engineering tests in the laboratory of the Ural company Prosoft-Systems. BioSmart terminals and readers will remain operational even in a rainstorm or when a fire alarm system is triggered.



2. On July 28, a two-day business mission of the Skolkovo Foundation to South Korea began. The event is held via videoconference and is organized with the support of the Korea-Russia Science and Technology Cooperation Center(KORUSTEC). Hyundai Motor, LG, Innopolis Foundation, NIPA, TIPA participated in the event and they with Skolkovo Foundation discussed the development of information and communication technologies in South Korea, the formation of an innovation ecosystem in the country and the specifics of building cooperation with large corporations.



3. The technology of the researchers of the Perm Polytechnic Institute will allow to reduce the weight of aircraft and missile structures and maintain their strength. Lighter products will reduce product costs and reduce fuel consumption. For this, researchers have proposed a method for designing structures in 2 stages. They sequentially processed the product blank using two well-known methods - topological and parametric optimization.



4. An international team of researchers with the participation of a student of the Faculty of Fundamental Physical and Chemical Engineering of Moscow State University has developed a new method for searching for genetic changes in chromosomes using computer vision. A team of researchers used 14 million images from The Cancer Genome Atlas (TCGA) dataset and these images made it possible to train the Inception-V4 neural network.



5. Experts in psychology and artificial intelligence from the Higher School of Economics, OGEU and BestFitMe (UK-Russia) have taught a cascade neural network to identify personality traits(extraversion, friendliness and willingness to compromise, conscientiousness and conscientiousness, and so on) from a photograph of a face. With further improvement of the algorithm, it can be used in the recommendation systems of online stores and HR departments of companies.



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