RUDN scientists have found out how to reduce the cost of flights to satellites
1200 spacecraft rotate in different orbits around the Earth. However, the period of their active existence is limited due to the short-lived on-board equipment, malfunctions and the inevitable fuel consumption. Classic maintenance schemes, when the service device is launched from the Ground, lead to huge costs. Such schemes are justified if the satellite is in orbit in a single copy and is of high value (for example, the Hubble telescope).
A team of RUDN scientists has found the best solution for servicing low-orbit groups that consist of dozens of satellites — it minimizes fuel consumption due to optimal maneuvering. Using the algorithm on board the service module will allow you to quickly and with high accuracy estimate the trajectory of the flight to the satellites for a limited time, taking into account the fuel supply on board the module.
"One of the primary tasks when creating promising space systems, along with technical implementation and solving legal issues, is the choice of the orbital construction of the system, the calculation of flight trajectories... We have created a number of high-speed algorithms and a software and mathematical apparatus for selecting the orbits of the space service system and analyzing its functioning according to various optimization criteria. Our algorithm is also applicable for assessing dangerous approaches to other satellites and space debris objects," Vladimir Razumny, Ph.D., Associate Professor of the Department of Mechanics and Mechatronics, Academy of Engineering, RUDN University.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.