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The list of national projects SAS

Institute of Informatics
Algorithm of collective intelligence: Interdisciplinary study of swarming behaviour in bats
Algoritmus kolektívnej inteligencie: Interdisciplinárne štúdium swarmového správania netopierov.
Program: SRDA
Project leader: Ing. Zelenka Ján PhD.
Annotation:Various algorithms of artificial intelligence inspired by real biological mechanisms are successfully applied in military and civil sector. In this proposed project, cooperative research of four scientific institutions having different basis, methodology and the object of study (biology, computer science and technology) focuses on interdisciplinary study of social self-organizational behaviour of tree-dwelling bats with the aim to develop new meta-heuristic method capable of space exploration. The project has a great potential to bring new scientific knowledge about mechanisms of collective intelligence in social structures of biological organisms, which will contribute to the field of theoretical biology, behavioural nad evolutionary ecology. Additionally, it will contribute to the field of artificial intelligence as it focuses on swarming behaviour of individuals/agents with higher nervous activity and well developed cognitive skills. The model organisms (bats) on which this project is focused are using advanced biological mechanism capable of state space exploration and at the same time preventing group disintegration. This specific characteristic has a great potential for development of new biologically inspired algorithms and methods applicable e.g. in movement coordination of unmanned aerial vehicles. Distinguished contribution of the project is R&D of ultra-light sensors applicable not only in biological research. The project originality is in interconnection of different research areas. Therefore it is important to review it interdisciplinary.
Duration: 1.8.2018 - 31.7.2022
Early Warning of Alzheimer
Early Warning of Alzheimer
Project leader: Ing. Rusko Milan PhD.
Duration: 1.9.2020 - 31.8.2023
Electron beam lithography of nanometer structures for 2D materials on the base of metal sulfides
Elektrónová litografia nanometrových štruktúr pre 2D materiály na báze sulfidov kovov
Program: VEGA
Project leader: Ing. Mgr. Andok Robert PhD.
Annotation:Motivation of this project comes out the research of new 2D materials such as metal sulfides and from the present state of development of e-beam lithography (EBL) as one of the alternative methods of 2D structures preparation in electronics. This project is focused on obtaining new scientific results in the patterning of nano-scale structures (10-100nm) in electron resists. Attention will be paid to the research of the influence of the electron lithography processes on the resulting nanometric patterns patterned in electron resits in term of resolution, dimensions accuracy and edge roughness of the structures in the resist. We will study the parameters influencing the profile of the nanometric patterns in polymeric resists. The simulations of lithographic parameters of electron resists on thin semiconductor layers, nitride membranes and layers with 2D materials, are an important part of this project. Based on the simulations of lithographic parameters, we will prepare nanometric structures on these materials.
Duration: 1.1.2018 - 31.12.2021
New Methods and Approaches for Distributed Scalable Computing
Nové metódy a prístupy pre distribuované škálované počítanie
Program: VEGA
Project leader: doc. Ing. Hluchý Ladislav CSc.
Annotation:Nowadays, there is a growing number of heterogeneous data from distributed sources, which brings great challenges to extract valuable knowledge from them. Current solutions are computationally-intensive modeling and simulations in a variety of science, industry and commercial areas through machine learning, neural networks, and deep learning. Due to the extremely multi-faceted dynamic data it is highly necessary to design novel methodologies, robust methods and approaches for scalable analytics in conjunction with scalable data collection, processing and management. High-performance platforms also need to be upgraded with the latest cloud technology knowledge for flexible management of large-scale systems. The project will also include research and development of appropriate tools and services for distributed and scalable information processing with the support for high-performance platforms. The proposed project builds on the results achieved in the VEGA 2/0167/16 project and in the four H2020 projects.
Duration: 1.1.2020 - 31.12.2022
Computer modelling of fire dynamics and effects
Počítačové modelovanie dynamiky požiaru a jeho dôsledkov
Program: VEGA
Project leader: RNDr. Glasa Ján CSc.
Annotation:Research in the suggested project is oriented on formulation of new scientific knowledge in the field of computer modelling of fire dynamics and effects. Huge societal damages on property, environment, destroyed buildings and infrastructure and threat for human lives and health caused by fires create acute need for such research of all-society importance. The research will utilize the authors‘ results and experiences on experimental testing of fires and investigation of applicability of models and program systems capable to simulate complex processes related to fire. The research will focus on computer simulation of fire course and consequences of chosen fire scenarios and its efficient parallel realization on high-performance computer systems.
Duration: 1.1.2020 - 31.12.2022
Processing of sensor data via Artificial Intelligence methods.
Spracovanie údajov zo senzorov prostriedkami umelej inteligencie
Program: VEGA
Project leader: Ing. Malík Peter PhD.
Annotation:The project will propose new methods and algorithms for processing of multi-sensor data for tasks of object diagnostics, areas of interest evaluation, secure communication and simplification of the new intelligent models creation. The research will focus on advanced methods of artificial intelligence with emphasis on deep learning. Artificial Intelligence algorithms show significantly better results than traditional methods, and an example of this is the tremendous progress of refining semantic image segmentation through deep learning over the last five years. Modern, low-cost, miniature electro-mechanical structures allow simple integration and group deployment of multiple sensors, resulting in the production of a huge amount of multi-sensor data that can not be manually processed. The project output will include new models of accurate semantic image segmentation, precision object modeling, multiple sensor collaboration models, and secure data transfer, especially for the Internet of Things and Industry 4.0.
Duration: 1.1.2019 - 31.12.2022
Sports Video And Statictics Automation System (SVASAS)
Systém pre automatizáciu videa a štatistík v športe
Program: EU Structural Funds Research & Development
Project leader: doc. Ing. Hluchý Ladislav CSc.
Duration: 1.6.2020 - 30.11.2022

The total number of projects: 7