– Currently solved projects of the department:
How to achieve real chemical precision in the exascale era
Targeting Real Chemical Accuracy at the Exascale (TREX)
Programme: Horizon 2020
Responsible researcher: prof. Ing. Štich Ivan, DrSc.
ID: H2020-952165
Duration: 1.9.2022 – 31.3.2024
Imaging data and services for aquatic science (iMagine)
Program: Horizon Europe
Responsible researcher: Ing. Tran Viet, PhD.
ID: 101058625
Duration: 1/9/2022 – 31/8/2025
EOSC Beyond: advancing innovation and collaboration for research
Program: Horizon Europe
Responsible researcher: Ing. Tran Viet, PhD.
ID: 101131875
Duration: 1.4.2024 – 31.3.2027
Integrated Technological and Information Platform for wildfire management (SILVANUS)
Programme: Horizon 2020
Responsible researcher: Ing. Zoltán Balogh, PhD.
ID: H2020-101037247
Duration: 1.10.2021 – 31.3.2025
Artificial Intelligence for the European Open Science Cloud (AI4EOSC)
Program: Horizon Europe
Responsible researcher: Ing. Tran Viet, PhD.
ID: 101058593
Duration: 1/9/2022 – 31/8/2025
Website: https://ai4eosc.eu/
Teveraging the European compute infrastructures for data-intensive research guided by FAIR principles (EuroScienceGateway)
Program: Horizon Europe
Responsible researcher: Ing. Tran Viet, PhD.
ID: 101057388
Duration: 1/9/2022 – 31/8/2025
Secure Interactive Environments for SensiTive data Analytics (SIESTA)
Program: Horizon Europe
Responsible researcher: Ing. Tran Viet, PhD.
ID: 101131957
Duration: 1.1.2024 – 31.12.2026
Manipulation of spin properties in 2D materials
Program: SASPRO
Responsible researcher: prof. Ing. Štich Ivan, DrSc.
ID: SASPRO 2 project no. 945478
Duration: 1.9.2022 – 31.8.2024
Semantic distributed computing continuum for extreme data processing
Program: VEGA
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 2/0131/23
Duration: 1.1.2023 – 31.12.2025
Study of electronic properties of 2D materials by ultra-accurate quantum Monte Carlo methods
Program: APVV
Responsible researcher: prof. Ing. Štich Ivan, DrSc.
ID: APVV-21-0272
Duration: 1.7.2022 – 30.6.2025
Artificial Intelligence for Personalized Oncology: from Single-Sample Assessment to Real-time Monitoring of Solid Tumours (AIPOLOGY)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-21-0448
Duration: 1.7.2022 – 30.6.2025
– Completed projects:
3D Visualization of Spatial Data
Agenda: Intergovernmental Agreement
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 53s07
Duration: 1.1.2006 – 30.11.2007
Website: http://ups.savba.sk/3dspatial/
Seamless Communication for Crisis Management (SeCriCom)
Program: 7RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-218123
Duration: 1.9.2008 – 30.4.2012
Website: http://en.wikipedia.org/wiki/Secricom
Data Fusion for Flood Analysis and Decision Support (ANFAS)
Program: 5RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: IST-1999-11676
Duration: 1.1.2000 – 28.2.2003
Website: https://cordis.europa.eu/project/rcn/53064/factsheet/en
EGI Advanced Computing for EOSC (EGI-ACE)
Programme: Horizon 2020
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: H2020-101017567
Duration: 1.1.2021 – 30.6.2023
Website: https://www.egi.eu/projects/egi-ace/
EGI: Integrated Sustainable Pan-European Infrastructure for Researchers in Europe (EGI-InSPIRE)
Program: 7RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-261323
Duration: 1.5.2010 – 31.12.2014
Website: www.egi.eu
European Open Science Cloud – Expanding Capacities by building Capabilities (EOSC-Synergy)
Programme: Horizon 2020
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 857647
Duration: 1.9.2019 – 31.10.2022
Data Fusion Grid Infrastructure
Program: INTAS
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 06-1000024-9154
Duration: 1.1.2007 – 31.12.2008
Hybrid Medical Complex Systems (SK-RO)
Agenda: Intergovernmental Agreement
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.1.2011 – 31.12.2012
Integrating and managing services for the European Open Science Cloud (EOSC-hub)
Programme: Horizon 2020
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 777536
Duration: 1.1.2018 – 31.3.2021
Interactive European Grid (int.eu.grid)
Program: 6RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP6-31857
Duration: 1.5.2006 – 30.4.2008
Website: grid.ifca.inican.es/int.eu.grid
Mediterranean Grid of Multi-Risk Data and Models (MEDIGRID)
Program: 6RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 4044
Duration: 1.11.2004 – 31.10.2006
Parallel Processing Tools: Integration and Result Dissemination (KIT)
Program: CIP-ICT
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 977100-PPTIRD
Duration: 17.7.1998 – 16.7.1999
Website: https://cordis.europa.eu/project/id/977100
High Performance Computing Tools for Industry, EU Copernicus (HPCTI)
Program: CIP-ICT
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: CP-93-5383
Duration: 1.10.1994 – 30.9.1996
Website: http://ups.savba.sk/parcom/sephp/sephp.html
Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud (DEEP-HybridDataCloud)
Programme: Horizon 2020
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 777435
Duration: 1.11.2017 – 30.4.2020
Website: http://deep-hybrid-datacloud.eu/
Development of machine learning models for high-performance computing
Program: Interacademic Agreement (MAD)
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.4.2020 – 31.12.2022
Development of software tools for analysis and synthesis of schedulers for cloud computing
Program: Interacademic Agreement (MAD)
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 6/4/2017 – 31/12/2019
A Platform for Organizationally Mobile Public Employees (Pellucid)
Program: 5RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: IST-2001-34519
Duration: 1.3.2002 – 31.12.2004
Website: http://agents.ui.sav.sk/index.php?n=Main.Projects https://cordis.europa.eu/project/rcn/61524/factsheet/en
COMMunity-based Interoperability Utility for SMEs (Commius)
Program: 7RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-213876
Duration: 1.2.2008 – 31.1.2011
Website: www.commius.eu
Advanced Data Mining and Integration Research for Europe (ADMIRE)
Program: 7RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-215024
Duration: 1.3.2008 – 28.2.2011
PROviding Computing solutions for ExaScale challengeS (PROCESS)
Programme: Horizon 2020
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 777533
Duration: 1/11/2017 – 30/10/2020
Website: http://www.process-project.eu/
Flood Forecasting Computed on Grid Infrastructures
Program: NATO
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 981032
Duration: 1.1.2004 – 31.12.2006
Programming environment for adaptive development of high performance parallel software on heterogeneous platforms (MAD with s ISS NASU, Kyiv)
Program: Interacademic Agreement (MAD)
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.1.2011 – 31.12.2013
– RAilway Network of Excellence
Program: European Science Foundation (ESF)
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: SORO/JPD 3-094/2005/NP1-033, 13120200104
Duration: 3.1.2007 – 31.12.2007
– Dissemination and Exploitation Grids in Earth Science (DEGREE)
Program: 6RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP6-034619
Duration: 1.6.2006 – 31.5.2008
Website: www.eu-degree.eu
European Urban Simulation for Asymmetric Scenarios (EUSAS)
Program: EDA
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: A-0938-RT-GC
Duration: 1.3.2010 – 31.8.2012
Social Network of Machines (SOON)
Program: ERANET
Responsible researcher: Ing. Zoltán Balogh, PhD.
ID:
Duration: 1.3.2019 – 30.4.2022
Software Engineering for Parallel Processing, EU Copernicus (SEPP)
Program: CIP-ICT
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: CIPA – CT93-0251
Duration: 1.2.1994 – 31.3.1997
Website: http://ups.savba.sk/parcom/sephp/sephp.html https://cordis.europa.eu/project/id/CIPA930251
Enabling Grids for E-scienE III (EGEE-III)
Program: 7RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-222667
Duration: 1.5.2008 – 30.4.2010
Website: www.eu-egee.org
Enabling Grids for E-Science in Europe (EGEE)
Program: 6RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 508833
Duration: 1.4.2004 – 31.3.2006
Website: www.eu-egee.org
Enabling Grids for E-scienCe II (EGEE II)
Program: 6RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: RI-031688
Duration: 1.4.2006 – 31.3.2008
Website: www.eu-egee.sk
Stimulation of European Industry through High Performance Computing, EU Copernicus Network (SEIHPC)
Program: CIP-ICT
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: COP-94-00774
Duration: 1.4.1995 – 31.3.1997
Website: https://cordis.europa.eu/project/id/CP94-774
Emergency Responder Data Interoperability Network (REDIRNET)
Program: 7RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7 – 607768
Duration: 1.3.2014 – 31.8.2016
Virtual Enterprises by Networked Interoperability Services (VENIS)
Program: 7RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7 – 284984
Duration: 1.9.2011 – 31.8.2015
Development of GRID Environment for Interactive Applications (CROSSGRID)
Program: 5RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: IST-2001-32243
Duration: 1.3.2002 – 30.4.2005
Website: https://cordis.europa.eu/project/rcn/63588/factsheet/en
Engaging the EGI Community towards an Open Science Commons (EGI-Engage)
Programme: Horizon 2020
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 654142
Duration: 1.3.2015 – 31.8.2017
Website: https://www.egi.eu/about/projects/
Knowledge-based Workflow System for Grid Applications (K-WfGrid)
Program: 6RP
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP6-511385
Duration: 1.9.2004 – 28.2.2007
Website: www.kwfgrid.net
– (ROAR-PP-H2020)
Rapid Operational Analytics for flood Response (ROAR-PP-H2020)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: PP-H2020-18-0017
Duration: 28.8.2018 – 31.12.2018
– (XPERT-PP-H2020)
Experimentation platform for the successful adoption of disruptive technologies in public services (XPERT-PP-H2020)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: PP-H2020-18-0012
Duration: 28.8.2018 – 31.12.2018
Adaptive Interoperability Framework for Private and Public Sector (AIIA)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-0216-07
Duration: 1.9.2008 – 31.12.2010
Website: http://aiia.ui.sav.sk/
Analysis of environmental influences on power industry equipment by the methods of artificial intelligence and cloud computing (ARIEN)
Program: APVV
Responsible researcher: Ing. Kvassay Marcel, PhD.
ID: APVV-20-0548
Duration: 1.7.2021 – 31.12.2023
Application platform for interactive grid applications
(INTAP)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: RPEU-0029-06
Duration: 15.2.2007 – 31.8.2008
Seamless communication for crisis management (SeCriCom-APVV)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: DO7RP-0007-08
Duration: 1.9.2008 – 31.12.2009
Seamless communication for crisis management (SeCriCom-MVTS)
Program: MVTS support from SAS funds
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.9.2008 – 31.12.2009
Center for the Research of Risks of Water Distribution in a Large City (CVR)
Programme: EU Structural Funds Research and Development
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26240220082
Duration: 1.7.2012 – 30.6.2015
Cloud Computing for Big Data Analytics (Clan)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-0809-11
Duration: 1.7.2012 – 31.12.2015
Website: clan.ui.sav.sk
Effective tools and mechanisms for grid reading
Program: VEGA
Responsible researcher: Ing. Tran Viet, PhD.
ID: 2/6103/6
Duration: 1.1.2006 – 1.12.2008
FaceControl – a complex communication device for innovative management of production and support processes in industry (FACECONTROL)
Programme: EU Structural Funds Research and Innovation
Responsible researcher: doc. Ing. Forgáč Radoslav, PhD.
ID: 313012P897
Duration: 1.3.2019 – 31.10.2020
Website: FACECONTROL_web.pdf
Intelligent methods for large-scale information processing
Program: VEGA
Responsible researcher: Doc. RNDr. Laclavík Michal, PhD.
ID: 2/0184/10
Duration: 1.1.2010 – 31.12.2012
Intelligent Cloud Workflow Management for Dynamic Metric-Optimized Application Deployment (ICONTROL)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-20-0571
Duration: 1.7.2021 – 31.12.2023
Intelligent technologies for knowledge-oriented organizations
Program: VEGA
Responsible researcher: Doc. RNDr. Laclavík Michal, PhD.
ID: VEGA 2/7098/27
Duration: 1.1.2007 – 31.12.2009
Website: http://ikt.ui.sav.sk/vega/
Cognitive traveling in digital space of the Web and digital libraries supported by personalized services and social networks (TraDiCe)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-0208-10
Duration: 1.5.2011 – 31.10.2014
Competence Center for SMART Technologies for Electronics and Informatics Systems and Services (KC-INTELINSYS)
Programme: EU Structural Funds Research and Development
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26240220072
Duration: 1.9.2011 – 30.6.2015
Manipulation, functionalization, electronic properties and bioapplications of 2D materials: 2D-MAT
Program: VEGA
Responsible researcher: Prof. Ing. Štich Ivan, DrSc.
ID: 2/0040/24
Duration: 1.1.2024 –
Methods and algorithms for the semantic processing of Big Data in a distributed computing environment
Program: VEGA
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 2/0167/16
Duration: 1.1.2016 – 31.12.2019
Tools for preparation, effective execution and visualization of applications and data management in the Grid environment (GRID-TOOLS)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: RPEU-0024-06
Duration: 15.2.2007 – 31.8.2008
Tools for acquiring, organizing and maintaining knowledge in the environment of heterogeneous information sources
Program: ŠPVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.9.2004 – 31.3.2008
Low-dimensional materials – manipulation, functionalisation and bioapplications: LOW-D-MATTER
Program: VEGA
Responsible researcher: prof. Ing. Štich Ivan, DrSc.
ID: 2/0070/21
Duration: 1.1.2021 – 31.12.2023
New Methods and Approaches for Distributed Scalable Computing
Program: VEGA
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 2/0125/20
Duration: 1.1.2020 – 31.12.2022
Optimization of recycling production lines by application of unconventional control methods. (OptiMAT)
Program: APVV
Responsible researcher: Ing. Zoltán Balogh, PhD.
ID: VMSP-016-09
Duration: 1.9.2009 – 31.8.2011
Center of Excellence for SMART Technologies, Systems and Services
Programme: EU Structural Funds Research and Development
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 26240120005
Duration: 1.5.2009 – 30.4.2011
Center of Excellence for SMART Technologies, Systems and Services II
Programme: EU Structural Funds Research and Development
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 26240120029
Duration: 1.1.2010 – 31.1.2014
COMmunity-based Interoperability Utility for SMEs (Commius-APVV)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: DO7RP-0005-08
Duration: 1.2.2008 – 31.12.2009
COMmunity-based Interoperability Utility for SMEs (Commius-MVTS)
Program: MVTS support from SAS funds
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.2.2008 – 31.12.2009
Advanced Data Mining and Integration Research for Europe (ADMIRE-APVV)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: DO7RP-0006-08
Duration: 1.3.2008 – 31.12.2009
Advanced Data Mining and Integration Research for Europe (ADMIRE-MVTS)
Program: MVTS support from SAS funds
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: FP7-215024
Duration: 1.3.2008 – 31.12.2009
Prediction and detection methods of significant and dangerous phenomena based on meteorological data mining
Data Mining Meteo (DMM)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: VMSP-P-0048-09
Duration: 1.9.2009 – 31.8.2011
Industry research in the area of effective work with large data in user-oriented applications (RECLER)
Programme: EU Structural Funds Research and Development
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26240220029
Duration: 1.5.2010 – 30.4.2012
Website: http://www.anasoft.com/sk/pages/Priemyselny-vyskum.shtml
Semantic composition of Web and Grid Services (SEMCO-WS)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-0391-06
Duration: 1.2.2007 – 31.12.2009
Service-based distributed computing and data management
Program: VEGA
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 2/0211/09
Duration: 1.1.2009 – 31.12.2011
Slovak infrastructure for high performance computing (SIVVP)
Programme: EU Structural Funds Research and Development
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26230120002
Duration: 15.1.2010 – 31.12.2015
Enabling Grids for E-scienE III (EGEE-III-MVTS)
Program: MVTS support from SAS funds
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID:
Duration: 1.5.2008 – 31.12.2009
Sports Video And Statics Automation System (SVASAS)
Programme: EU Structural Funds Research and Innovation
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: NFP313020U867
Duration: 1.6.2020 – 31.5.2021
Urgent Computing for Exascale Data (U-COMP)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-17-0619
Duration: 1.8.2018 – 31.12.2020
Virtual and constructive modeling, training and simulation of crowd behavior in urban environment (Riot)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: APVV-0233-10
Duration: 1.5.2011 – 31.10.2014
Selected methods, approaches and tools for distributed computing.
Program: VEGA
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: 2/0054/12
Duration: 1.1.2012 – 31.12.2015
Research and development of new information technologies for predicting and solving crisis situations and the safety of the population (CRISIS)
Programme: EU Structural Funds Research and Development
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26240220060
Duration: 3.1.2011 – 31.12.2013
Research and development of a knowledge system to support work flow management in organizations with administrative types of processes (REPORT)
Program: APVV
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: APVT-51-024604
Duration: 1.2.2005 – 31.12.2007
Research on the application of artificial intelligence tools in the analysis and classification of hyperspectral sensing data (HYSPED)
Programme: European Regional Development Fund (ERDF)
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: NFP313011BWC9
Duration: 1.2.2022 – 31.12.2023
Research of technologies for management of business processes in heterogeneous distributed systems in real time with the support of multimodal communication (RPKOM)
Programme: EU Structural Funds Research and Development
Responsible researcher: doc. Ing. Hluchý Ladislav, CSc.
ID: ITMS 26240220064
Duration: 3.1.2011 – 30.6.2014
PFO-CAD CP93: 7896 – Copernicus program – Geometric Modeling for CIM-oriented Virtual Reality
Program: Other
Responsible researcher: Ing. Sebestyénová Jolana, PhD.
ID: CP93:7896
Duration: 1.2.1994 – 30.4.1995
Website: http://cordis.europa.eu/project/rcn/30200_en.html
Imaging data and services for aquatic science (iMagine)
Abstract: The iMagine project will provide a portfolio of imagery datasets with free-of-charge, at-the-point, high-performance artificial intelligence (AI)-based image analysis tools and a Good Practices for Scientific Image Analysis document. These services and material will enable better and more efficient processing and analysis of marine image data. and freshwater research, accelerating our scientific knowledge of processes and measures relevant to healthy oceans, seas, coastal and inland waters. Building on the European Open Science Cloud (EOSC) computing platform, the project will deliver a general framework for developing, training and deploying AI models that can be adapted by researchers to fine-tune their AI applications for water pollution mitigation, biodiversity and ecosystem studies, climate change analysis and beach monitoring and also for the development and optimization of other AI applications in this area. The computing layer of iMagine consists of providers from the pan-European federated infrastructure EGI, together providing more than 132’000 GPU-hours, 6’000’000 CPU-hours and 1500 TB -months for storing and processing images. The iMagine AI framework will provide neural networks, parallel processing of very large data and analysis of massive online data streams in a distributed environment. 13 Research Infrastructures (RIs) will share over 9 million images and 8 AI-based applications through this framework. Having representatives from so many RI and IT experts developing a portfolio of compelling image processing services together will lead to the writing of Best Practices. Synergies between water applications will lead to joint solutions in data management, quality control, performance, integration, provenance and FAIR (Findable Accessible Interoperable Reusable) contributing to harmonization between RIs and providing inputs for iMagine Best Practices. The project outputs will be integrated and bring important contributions from RI and e-infrastructures to EOSC and AI4EU (Europe’s AI-on-Demand Platform).
EOSC Beyond: advancing innovation and collaboration for research
Abstract: The overall goal of the EOSC Beyond project is to support open science and research innovation in the context of the European Open Science Cloud (EOSC) by providing new core EOSC functions that will enable scientific applications to search, create and access multiple open science resources and offer them to researchers as integrated functions. The goal of the project is to accelerate new scientific applications using software adapters and to enable the principles of open science with machine composability and dynamic deployment of shared resources. The project also aims to support the innovations of the EOSC initiative by means of a test and integration environment, as well as to align the architecture and specifications of the EOSC core with the aim of integration with European data spaces.
Integrated Technological and Information Platform for wildfire management (SILVANUS)
Annotation: The project was submitted to call H2020-LC-GD-2020-3 Building a low-carbon, climate resilient future: Research and innovation in support of the European Green Deal. During the climate crisis, forest fires are becoming more dangerous and more frequent. The goal of the SILVANUS project is to offer a new innovative technological solution for improving forest fire preparedness and prevention. The key output of the project is the creation of a platform for forest management, including increasing resilience to climate change and preventing and suppressing forest fires. SILVANUS connects experts from the field of environment, technical and social sciences in order to help and support the regional and national authorities responsible for the management of forest fires in the respective countries. Along with the development of intelligent models of fire ignition and spread based on climate and weather data, SILVANUS will engage stakeholders in given regions to assess fire risk indicators. At the same time, new firefighter training methodologies will be developed using VR (virtual reality) and AR (augmented reality) tools, and real life environments and scenarios will be simulated.
Artificial Intelligence for the European Open Science Cloud (AI4EOSC)
Abstract: The AI4EOSC project will provide an extended set of advanced services for artificial intelligence (AI), machine learning (ML) and deep learning (DL) model development and application development in EOSC (European Open Science Cloud). These services will be combined into a complex platform providing advanced functions such as distributed, federated and split learning; new metadata source for AI/ML/DL models; event-driven services for data processing, or also the provision of AI/ML/DL services based on the so-called serverless computing. The project will use the results of the DEEP-Hybrid-DataCloud project and use the EOSC computing platform with its services, and in addition will offer the possibility to adapt this platform for the ever-changing needs of users. The main result of the AI4EOSC project will be a measurable increase in the number of advanced, high-level customizable services, available through the EOSC portal, serving as a catalyst for researchers to facilitate collaboration, ease access to high-end pan-European resources and reduce time to results; with a specific contribution to the perspective of the use of EOSC creating a new path to support the building of community practice of AI and ML in EOSC.
leveraging the European compute infrastructures for data-intensive research guided by FAIR principles (EuroScienceGateway)
Abstract: In the past decade, several scientific domains have been transformed into data-driven disciplines dependent on the exchange and integration of internationally distributed data. Exploiting this data is still cumbersome and largely manual work prone to loss and error, increasingly specialized beyond the technical capabilities of most users. They encourage us to FAIR (Findable Accessible Interoperable Reusable) practices, but the adoption curve is steep. The needs of computing and data resources, tools and application platforms are often domain specific. Many scientists are trying to navigate this complex ecosystem. In general, researchers do not have the computing skills to effectively use the HPC or cloud platforms they need. Therefore, new approaches are needed to enable all researchers to use a wide range of digital skills to effectively use the various computing infrastructures available in Europe for asynchronous and interactive applications. The project will use a distributed computer network in 13 European countries, accessible through 6 national user-friendly web portals facilitating access to computing and storage infrastructures in Europe as well as to data, tools, workflows and services that can be adapted to the needs of researchers. Workflows will be integrated into the EOSC core. Adapting, developing and implementing technologies to work together across services will enable researchers to produce high quality FAIR data for everyone in EOSC. The communities of scientific disciplines – life sciences, climate and biodiversity, astrophysics, materials science – will make a bridge from EOSC-technical services to scientific analyses. EuroScienceGateway will deliver a robust, scalable, seamlessly integrated open infrastructure for data-initiated research, contributing an innovative and adaptable service to EOSC , which will enable operationally open and FAIR data and their processing, will move European scientists to a new digital age of science.
Secure Interactive Environments for SensiTive data Analytics (SIESTA)
Abstract: The SIESTA project will provide user-friendly tools to support the expansion of sensitive data sharing and processing in EOSC. The project will provide a trusted cloud-based environment for managing and sharing sensitive data that is built in a reproducible way, together with a set of services and tools to facilitate secure sharing of sensitive data in EOSC through state-of-the-art anonymization techniques. The overall goal of the project is to extend EOSC Exchange services by providing a set of trusted cloud environments for analyzing sensitive data in EOSC that demonstrate the feasibility of FAIR data principles on top of them.
Semantic distributed computing continuum for extreme data processing
Abstract: Since the beginning of the era of big data, a number of approaches to its processing have been developed. Nevertheless, due to the continuous and extremely high speed of data generation, such data cannot be effectively analyzed even with the help of advanced scientific tools. Currently, it is necessary to work with big data not only in a high-performance cloud environment, but also in a less powerful, highly distributed “edge” peripheral environment (for example, the Internet of Things, sensors, etc.). The requirements for analysis are becoming more extreme in the sense that, for example, as a result of highly distributed data in the edge-cloud continuum, incomplete data sets arise, new data security requirements and others. The solution to the above-mentioned issue cannot be concentrated only on data. Extreme data analysis requires extreme data networks enabling intelligent execution of tasks in the edge-cloud continuum to minimize the movement of big data and maximize the use of resources located near the data, thereby increasing its security.
Artificial Intelligence for Personalized Oncology: from Single-Sample Assessment to Real-time Monitoring of Solid Tumours (AIPOLOGY)
Abstract: Oncology of the 21st century has changed by becoming dependent on the processing of big data in determining the optimal treatment of the patient. However, this approach is still unable to negate some basic limitations resulting from the fact that tumors are heterogeneous, their analysis is both financially and time-consuming, and in most cases only one temporal snapshot of tumor evolution is analyzed. However, with the deployment of monitoring methods based on liquid biopsy, we are getting into a situation where it is possible to monitor the state of cancer in real time, but most of the existing algorithms were not designed for this eventuality at all. The presented AIpology project tries to keep up with the times by designing and implementing new algorithms of artificial intelligence and statistical learning, which will propose optimal treatment of an oncological patient based on available therapeutically targetable mutations, which will be interpreted with regard to which tumor cell clones are found, what are the relationships between individual clones and with regard to how the given tumor structure will develop over time. The proposed system will be able to explain why and when the tumor becomes resistant to the selected therapy and suggest possible ways to proceed when this happens. The AIpology project is based on our group’s research, which has been going on for over a decade and dates back to the first tumor genome decoding studies at the University of Oxford, where we were present.
Completed projects (annotations):
3D visualization of spatial data
3D Visualization of Spatial Data
Annotation: The 3D spatial data visualization project loosely follows on from the Medigrid project, the goal of which was to create a system of web services for running simulations of environmental disasters and the project for simulating forest fires in Slovakia. The goal of the project is to use data and simulation outputs obtained within the mentioned projects to create three-dimensional models of natural disasters (floods, forest fires, erosion and landslides). A requirement was established that the models should be viewable on a regular PC and on a virtual reality device (CAVE).
EGI Advanced Computing for EOSC (EGI-ACE)
Abstract: The mission of the EGI-ACE project of the EGI initiative is to implement a European cloud computing platform for open science by providing secure federated cloud computing and storage facilities in cooperation with providers from the EGI federation, with commercial providers, with data providers and with international research infrastructures of pan-European relevance.
European Open Science Cloud – Expanding Capacities by building Capabilities (EOSC-Synergy)
Abstract: EOSC-synergy will extend EOSC coordination to the 9 countries of the project solvers by harmonizing policies and involving national research e-infrastructures, scientific data and thematic services, thus filling the gap between national initiatives and EOSC. The project will introduce new possibilities by making national thematic services available throughout Europe by expanding EOSC offers for environmental, climate change, earth observation and life sciences. This will be supported by capacity expansion by federating computing, data and storage resources in line with EOSC and FAIR policies and practices. The project will advance the state of EOSC in software and services using a quality-driven approach to service integration and promote convergence and alignment with respect to EOSC standards and best practice. . At the same time, it will expand training and educational EOSC activities by introducing an online platform aimed at increasing the development of skills and competences. EOSC-synergy complements the ongoing activities in the EOSC-hub project and other related projects by linking national institutions and infrastructures to their future management, data and coordination national projects.
Hybrid Medical Complex Systems
Hybrid Medical Complex Systems (SK-RO)
Annotation: APVV COST SK-RO-0014-10
Integrating and managing services for the European Open Science Cloud (EOSC-hub)
Abstract: The EOSC-hub project creates an integration and management system of the future European Open Science Cloud (Open Science Cloud), which provides a catalog of services, software and data from the EGI-federation, EUDAT CDI, INDIGO-DataCloud and from the main research e-Infrastructures. – the management system (Hub) is based on advanced processes, policies and tools of leading European federal e-Infrastructures to cover the entire life cycle of services, from their planning to launch. The “Hub” concentrates services from local, regional and national e-Infrastructures in Europe, Africa, Asia, Canada and South America. The “Hub” functions as a single point of contact for researchers and innovators to find, access, use and reuse a wide range of resources for advanced data-driven research. Thanks to the virtual access mechanism, more research communities and users will have access to services supporting their scientific research and inter-disciplinary and international cooperation. By providing specialized training, the project will improve the skills and knowledge of researchers and service operators, as well as by establishing competence centers in order to co-create solutions with users. The private sector will be involved by creating a “Joint Digital Innovation Hub”, which stimulates the ecosystem of industry/SMEs, providers services and researchers to support business pilot projects, market launch and strategies for better commercial use. The EOSC-hub builds on existing technologies that are already at TRL 8 level and addresses the need for interoperability by promoting the adaptation of open standards and protocols. By mobilizing e-Infrastructures including more than 300 global data centers of 18 pan-European infrastructures, the project is a breakthrough milestone for the implementation of the European Open Science Cloud.
Tools for parallel information processing: Integration and further extension of results
Parallel Processing Tools: Integration and Result Dissemination (KIT)
Abstract: The SEPP consortium wrote a book that was published by Nova Science (USA).
Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud (DEEP-HybridDataCloud)
Abstract: A key concept in the “DEEP Hybrid DataCloud” project is the need to support intensive computing technologies to explore very large data that require specialized high-performance hardware such as graphics accelerators or low-latency links. The hybrid cloud makes it possible to make available such resources that are not easily available to researchers in the required scope in the current EU e-infrastructure. At the same time, we propose to deploy a set of building blocks under the collective name “DEEP as a Service”, which will enable the easy development of applications requiring the following technologies: deep learning based on neural networks, parallel post-processing of very large data and analysis of massive data flows. Three pilot applications using very large datasets in biology, physics and network security are designed. And pilots for dissemination to other industries such as medicine, Earth observation, astrophysics and social sciences will be supported in a test environment with significant use of high-performance computing resources, including the latest generation accelerators, to evaluate the performance and scalability of the proposed solutions. We will implement a “DevOps” approach to prove the quality of delivered software and services, which will also be offered to developers of research applications. The project will upgrade to TRL8 the existing services and technologies from TRL6+, including relevant contributions to EOSC from H2020 of the INDIGO-DataCloud project, which will be enriched with new functionality that is now only available as prototypes, namely support for graphics accelerators and low-latency communications. These services will be deployed in the project’s test environment, offered to the research communities connected to the project through pilot applications and integrated into the EOSC framework, where they can be further scaled in the future.
Development of software tools for analysis and synthesis of schedulers for cloud computing
Abstract: Modern scientific tasks need a large amount of computing resources, and therefore their optimization in a multiprocessor environment is a very important problem. In the project, we will focus on cloud systems, which is one of the newest and most important areas of high-performance computing. One of the main features of cloud computing is high heterogeneity. It is common to have a single physical server running many simulations from different users competing for resources. In most cases, especially in the public cloud, the user is not able to influence the distribution of resources. The inefficiency and error rate of allocation algorithms can cause a significant increase in the time required to process a given task, therefore, one of the key elements of cloud computing is efficient algorithms, enabling flexible and stable allocation of resources. The main problem they face is unfair and unequal access to resources. Users and their roles are diverse, so the user becomes an agent trying to increase his share of resources. This can lead to the inefficiency of a given system, therefore, a key element of cloud computing is efficient load distribution algorithms – scheduling and negotiation services providing resources to system users. The main idea of the project is to apply approaches from game theory to the problem of planning and allocating computing resources in a dynamic heterogeneous environment in which individual users compete for computing resources. Subsequently, we want to focus on optimizing access to computing resources, which will respect the requirements of end users. We will model this task as a multi-criteria optimization. Each criterion will be assigned a weight that will express its priority. In this way, it will be possible to adapt the optimization to the needs of end users. We will tackle this task in such a way that we are able to support different cloud service providers. This project is a continuation of the previous cooperation of our institute in the research of adaptation methods for programming high-performance computing resources consisting of heterogeneous multiprocessor systems.
A Platform for Organizationally Mobile Public Employees (Pellucid)
Abstract: The purpose of the project is to develop a flexible and adaptive platform to help employees who move between different public administration organizations at its middle and higher levels. Organizational mobility, when employees move from one department or organizational unit to another, is becoming an increasingly common phenomenon and brings its own challenges as well as opportunities. The Pellucid platform is a multi-level system, based on software agent technology, that helps these employees to collect, reuse and share knowledge and experience, thus benefiting them and the efficiency and effectiveness of the organization. The platform will use such technologies as autonomous cooperating agents, organizational memory, workflow and process modeling, metadata access to stored documents. The platform will be evaluated at pilot sites. It will be adaptable to a wide range of public administration organizations, so the prospects for its use are excellent.
COMMunity-based Interoperability Utility for SMEs (Commius)
Annotation: The Commius project solves inter-company connection (interoperability) for small and medium-sized enterprises based on the vision of ISU (Interoperability Service Utility), where the infrastructure to support interoperability should function in such a way that it is generally available, guaranteed and not owned by a specific entity. Commius solves this problem by building interoperability over the infrastructure that is present in organizations – email and web. ÚI SAS solves the system part of the interoperability of the connection to the email infrastructure as well as intelligent text processing and semantic annotation.
PROviding Computing solutions for ExaScale challengeS (PROCESS)
Annotation: Demonstrators of the PROCESS project will pave the way to “exascale” data services that will accelerate innovations and maximize the benefits of emerging data solutions. The most tangible output of the PROCESS project will be five prototypes of data services for processing very large data, implemented using advanced, modular, generalizable open source solutions for user-friendly exascale data. The services will be thoroughly validated in real conditions, both in scientific research and in industrial pilot deployment. In order to achieve these ambitious goals, the consortium of project solvers will bring together key players in a new data-driven ecosystem: the most important centers of high-performance computing and large data centers, communities such as the Square Kilometer Array (SKA) project – with unique data challenges that current solutions do not know satisfy and experienced e-Infrastructure providers with extensive experience in rapid application development. Moreover, in addition to providing service prototypes that can handle very big data, PROCESS fulfills the objectives of the work program (H2020) by using tools and services with heterogeneous case studies, including medical informatics, air transport revenue management and open data for global disaster risk reduction. This diversity of user communities will ensure that we not only support the movers, but that the solutions facilitate learning for the widest possible range of user communities. In addition, the chosen open strategy maximizes the potential for its use, together with mature software engineering practices that minimize the effort required to set up and maintain services based on the resulting software of the PROCESS project.
– RAilway Network of Excellence
Abstract: Creation of a network of excellence in the railway sector of the Bratislava region, which will participate in European Union support programs in the future. The activity fulfills the global goal of supporting the development of the competitiveness of the region through the development of human resources (JPD BA Goal 3).
Dissemination and Exploitation Grids in Earth Science (DEGREE)
Abstract: The DEGREE project is a Specific Support Activity (SSA) that aims to help promote the Grid across the large and diversified Earth Science community to increase awareness and understanding of Grid technologies and Grid infrastructure across the European Earth Science industry and research communities. Earth.
Simulation of behavior for asymmetric scenarios in urbanizations
European Urban Simulation for Asymmetric Scenarios (EUSAS)
Annotation: European Defense Agency, JIP-FP Call 4
Social Network of Machines (SOON)
Annotation: The project is focused on the influence of autonomous social agents on the optimization of production within the Industry 4.0 concept. A social agent represents a cybernetic-physical entity that optimizes the production process in an autonomous mode, imitating the behavior of people on social networks. Currently, the concept of Industry 4.0 is already counting on the existence of smart devices. However, in reality, these smart devices cannot communicate with each other, even within a single freak workshop. The project is motivated by the idea that if we want to create a real Internet of Things that connects devices, processes, data and people, all these entities must be connected within a single paradigm. In this project, we propose a holistic multi-agent paradigm that will connect machines and humans. The presence of human operators is key to the processes of learning and training sw agents, while deep learning and data mining algorithms will be used. Agents will make decisions based on the analysis of extensive and heterogeneous data collected from production processes – sensory data (temperature, vibrations, etc.), data from control systems (resource planning, MES, etc.) and data provided by operators in real time. Design and evaluation of the system will be carried out in close cooperation with three production companies (SK, ES, CH). In the project, we will focus on the tasks of predictive maintenance, which is currently an actual and so far insufficiently solved problem in manufacturing companies. The project has ambitions to bring significant innovations for digital businesses.
Enabling Grids for E-scienCe II (EGEE II)
Abstract: The goal of the EGEE integrated infrastructure is to enable the expansion of e-science applications, which will support the European Research Area (ERA), by creating and connecting Grid technology. To achieve these goals, the project* will integrate the technological development of the Grid within Europe and beyond* continue to maintain the European Grid infrastructure for science and industry with a focus on heterogeneity and interoperability with other Grid initiatives (US NSF Cyberinfrastructure)* will enable the creation of e- sciences for a spectrum of scientific and industrial institutions; other applications already use the EGEE infrastructure and their number will increase (LHC particle physics, biomedical, earth sciences, astrophysics, computational chemistry, fusion, geophysics,… )* adapt the middleware and train the scientific communities in ERA in using the Grid.
Emergency Responder Data Interoperability Network (REDIRNET)
Abstract: During the past 5 years, most of the REDIRNET project partners have been partners in the international SECRICOM and FREESIC projects, including a large number of high-ranking representatives of first responder organizations from various EU countries. An important result of this effort was the finding that, in addition to the interoperability of communication systems, there is a fulfilling need for the interoperability of other IT systems such as databases, sensor systems or cameras. REDIRNET aims to find solutions to satisfy this need. REDIRNET’s aim is to develop a decentralized platform for the cooperation of systems of organizations focused on saving life and property. REDIRNET will provide a meta-data gateway controlled from REDIRNET collaboration-web, a web-based tool for organization collaboration. The institutions involved will thus be able to establish partnerships with other organizations according to their operational needs. The cooperation web tool will provide them with the possibility of managing the scope of cooperation with partner entities. Participating organizations will develop a single adapter (for the REDIRNET gateway) and gain multilateral interoperability with partner organizations, which means high efficiency of invested resources on their side.
Engaging the EGI Community towards an Open Science Commons (EGI-Engage)
Abstract: EGI-Engage aims to accelerate the progress of the European Grid Infrastructure (EGI) in the field of strategy, policies, business and technical innovation, in the field of user engagement towards special areas of science and research, towards domain-specific research communities, research infrastructures within of the ESFRI roadmap, as well as within SMEs and industry. Within the project, ÚISAV solves the specific task of “accelerated computing in the cloud”, i.e. the integration of GPGPU accelerators into the EGI computing infrastructure.
Knowledge construction of work flow in Grid applications
Knowledge-based Workflow System for Grid Applications (K-WfGrid)
Annotation: .
- (ROAR-PP-H2020)
Rapid Operational Analytics for flood Response (ROAR-PP-H2020)
Annotation: Reimbursement of costs associated with the submission of the H2020 project, which was successfully evaluated, but was not approved due to lack of financial resources. - (XPERT-PP-H2020)
Experimentation platform for the successful adoption of disruptive technologies in public services (XPERT-PP-H2020)
Annotation: Reimbursement of costs associated with the submission of the H2020 project, which was successfully evaluated, but was not approved due to lack of financial resources.
Adaptive Interoperability Framework for Private and Public Sector (AIIA)
Abstract: Existing software solutions for interoperability (or automatic connection based on information technology) between companies or public organizations are mainly suitable for large companies. There is a lack of cheap, easily integrated and adaptive software solutions to support interoperability. One possibility is to create such solutions on top of the existing information and communication infrastructure that is available in most organizations. It is mainly electronic mail (email) and the web. In the AIIA project, we propose to create an adaptive solution to support interoperability using email communication, which is ubiquitous and is used daily by many people to perform various tasks that ultimately have to be performed manually. AIIA can have a significant impact on solving interoperability tasks, because it does not force users to change the software work tool (they can use email), they can also use the existing information and communication infrastructure in the organization as well as quickly adapt the platform for other application-dependent tasks. AIIA can also be used appropriately in the public sector to support eGovernment, where it can help solve the current problem of connecting public organizations. This is particularly pronounced in the countries of Eastern Europe, including Slovakia, where the public and state administration has a basic information and communication infrastructure – email and web, but does not have built-in solutions for connecting information systems.
Analysis of environmental influences on power industry equipment by the methods of artificial intelligence and cloud computing (ARIEN)
Annotation: The main goal of the ARIEN project is the design and verification of a new innovative method for determining the degree of environmental pollution for the needs of the energy industry, using data from the Slovak Hydrometeorological Institute. It will be based on advanced techniques of artificial intelligence, cloud computing and data integration, and has not yet been used in the Slovak energy sector. It will make it possible to effectively prevent breakdowns on 110 kV to 400 kV power lines due to voltage jumps. The results obtained by the new methodology will help to optimize the design of isolators at the design stage, during operation they will allow to improve the performance of maintenance. The use of artificial intelligence for the design methodology is a logical choice, because the processes of the spread and fall of impurities in the air and their chemical interactions cannot yet be satisfactorily described by classic physico-chemical models due to their complexity. Artificial intelligence tools and neural networks can find new unknown connections between input and output data. However, neural networks require large sets of training data, and therefore the second goal of the project is the design of a methodology for obtaining a sufficiently robust set of synthetic data for their training and testing. near insulators. During its development, the experience of the partner project VUJE with the operation of measurement systems installed on phase conductors, capable of working during the operation of power lines, will be used. The goals of the project reflect the current priorities of European research and the urgent needs of the Slovak energy industry, since in 2015 the standard STN 33 0405, which regulated the issue of pollution of insulators of external high-voltage lines and the period of their cleaning. The new methodology will make it possible to replace the usual process according to this standard, which is logistically, technically and time-consuming, with a new innovative procedure using available information processed by the most modern methods.
Seamless communication for crisis management (SeCriCom-APVV)
Annotation: Co-financing of RD activities of the relevant 7RP project up to a maximum of 25% of the RD activity budget. In the report for 2010, we report this project only as another financial source of the relevant 7RP project, even though the contract with APVV is signed until 04/30/2012.
Seamless communication for crisis management (SeCriCom-MVTS)
Annotation: Support mainly to cover non-claimable expenses such as VAT expenses of the relevant 7RP project and to improve especially travel expenses. The new MVTS rules valid since 2010 do not allow financing this project, even if the MVTS contract is valid until 30.4.2010.
Center for the Research of Risks of Water Distribution in a Large City (CVR)
Annotation: OPVaV-2011/4.2/07-SORORealization of top industrial research of an international level in the field of water supply risks by combining the capacities of the business and academic sectors.
Cloud Computing for Big Data Analysis
Cloud Computing for Big Data Analytics (Clan)
Annotation: VV2011
Efficient tools and mechanisms for grid computing
Annotation: Computing Grids have seen rapid development in recent times. Although the main domain of their use is mainly the field of science and research, organizations from commercial areas, such as industry, banking or medicine, are also interested in the computing capacity that Grids provide. However, there are many areas in grid computing that need to be improved in order to use Grids more efficiently: security, workflow management, data management. The goal of this project is the analysis and proposal of improving the basic properties of grid computing and a contribution to the creation of tools for the effective use of grid computing.
FaceControl – a complex communication device for innovative management of production and support processes in industry (FACECONTROL)
Annotation: The main goal of the FACECONTROL project (313012P897, OPVaI-MH/DP/2017/1.2.2-12) is to support research and development and innovation activities for the purpose of high-level product innovation applicable within the industrial revolution “Industry 4.0”. The project is aimed at for product innovation consisting in the development and subsequent production of the FaceControl product – a complex communication device oriented to the management of production and support processes in industry.
Intelligent methods for large-scale information processing
Abstract: Currently, more and more information is available in digital form. However, the increase in the amount of information also leads to so-called information overload. That is, to the availability of a lot of information, which, however, we cannot properly sort, integrate or search in it. The largest group of digital data is data created by humans such as: text, documents, images, video. With the advent of web 2.0 applications as well as the electronicization of banking or travel transactions, a lot of structured data is generated, which contains a lot of information, especially about the connections between real-world objects and digital objects. However, this valuable information is difficult to find and sort in the amount of available data. The project deals with the research and development of such methods that should partially enable this. At the same time, it focuses on the analysis, creation and verification of such methods and algorithms for processing information that are able to process, manage, search and make available extensive information resources.
Intelligent Cloud Workflow Management for Dynamic Metric-Optimized Application Deployment (ICONTROL)
Abstract: ICONTROL is a platform for dynamic and intelligent, function-based deployment of application workflows and their dynamic changes during runtime in hybrid edge-cloud computing environments. ICONTROL automatically constructs and deploys complex, workflow-based applications. ICONTROL will use semantic information about the available functionalities of cloud applications to automatically generate complex workflows of functions that will be performed with the help of cloud and edge resources. It will help users automate feature selection, configuration and deployment, resolving runtime failures and performance issues with automatic redeployment. In order to remove obstacles in the use of complex applications composed of workflows of functions for users who are not cloud experts, ICONTROL will support the separation of tasks into three categories of specialization. Cloud application developers will develop applications, semantically annotate and describe them. Algorithms based on artificial intelligence will help domain experts create applications as workflows composed of functionality provided by developers, using techniques of semi-automatic construction of workflows using semantic descriptions of functions. Application users will have the opportunity to choose workflows to deploy and run their applications, using the automation of the proposed system, in complex cloud and edge environments, without the burden of complex details of workflow selection, application deployment, error resolution or ensuring sufficient resources. ICONTROL will significantly improve the composability and adaptability of applications as workflows in the entire spectrum of edge acloud, from remote wireless IoT sensors, through personal devices to large computer centers, by creating a semantically enriched, platform-independent and secure platform for developing and running workflows of the FaaS (Function as a Service) paradigm, with automatic selection and using infrastructure resources.
Intelligent technologies for knowledge-oriented organizations
Abstract: An important factor in building a knowledge-based economy is the organization’s ability to evaluate its knowledge capital. Technologies and knowledge are becoming a key factor in increasing productivity. Therefore, companies support knowledge and experience management projects in their organizations and try to make the best possible use of knowledge capital. The goal of the project is to support the shift of companies to a knowledge-based economy by expanding existing and creating new models, algorithms, technologies and tools that can help organizations gradually transform into knowledge-oriented corporations. The basis of such a shift is the analysis and processing of information resources in organizations, which are mainly documents, electronic communication and databases, for the purpose of managing, creating, making available and sharing relevant information and knowledge. The project mainly focuses on the areas of knowledge modeling, service-oriented architectures, distributed knowledge bases, semantic annotation, knowledge mining, reasoning using cases and statistical methods. Special emphasis is placed on the processing of information resources in the Slovak language, where techniques based on neural networks will be used networks and ontologies.
Competence Center for SMART Technologies for Electronics and Informatics Systems and Services (KC-INTELINSYS)
Annotation: Strengthening cooperation in research and development between the economic and academic spheres by creating a competence center focused on intelligent technologies. Creating a competence center for industrial research and development in the field of intelligent technologies. Industrial research in the field of sensor systems, control and robotic systems and in the field of electronic services.
Methods and algorithms for the semantic processing of Big Data in a distributed computing environment
Annotation: The scientific research in the proposed project follows on from the research results achieved in the 7RP projects, in the solution of which most of the researchers took part: ADMIRE: Advanced Data Mining and Integration Research for Europe (2008-2011), Commius: Community-based Interoperability Utility for SMEs (2008 -2011), VENIS: Virtual Enterprises by Networked Interoperability Services (2011-2015) and EGI-InSPIRE: Integrated Sustainable Pan-European Infrastructure for Researchers in Europe (2010-2014). Several case studies from the mentioned projects created a motivational basis for scientific research in the field of semantic processing of big data in a virtual computing environment. A big challenge in the proposed project will be to research new methods, approaches and algorithms. The proposed project also builds on the scientific results achieved in two VEGA projects: Selected methods, approaches and tools for distributed information processing (2012-2015) and New methods and approaches for information processing and creation of knowledge bases. (2013-2015).
New Methods and Approaches for Distributed Scalable Computing
Abstract: Currently, the amount of heterogeneous data from distributed sources is increasing, which also brings challenges for extracting valuable knowledge from them. Current solutions are computationally intensive modeling and simulations in various scientific, industrial and commercial fields using machine learning, neural networks and deep learning. Considering the incoming dynamic data, which can be characterized as extreme from many points of view, it is necessary to design methodology, robust methods and approaches for scalable analytics in conjunction with scalable data collection, processing and management. It is also necessary to modernize high-performance platforms using the latest knowledge of cloud technology for flexible management of large-scale systems and platforms. The project will also include research and development of suitable tools and services for distributed and scalable information processing with the support of high-performance platforms. The proposed project builds on the scientific results achieved in the VEGA 2/0167/16 project and in 4 H2020 projects.
Optimization of recycling production lines by application of unconventional control methods. (OptiMAT)
Annotation: The subject of the project solution is the proposal of new approaches for optimizing the management and planning of the production process of plastic recycling by applying research in the field of unconventional management methods with a focus on the specifics of production lines for plastic recycling based on polymerization, on static and dynamic simulation and optimization of such models of production lines, detection of critical points, verification of throughput, control of collision conditions, timing and for simulation and optimization of material flows. An important task in the optimization of the production line will be the sensitive analysis of selected input and output parameters.
Center of Excellence for SMART Technologies, Systems and Services
Abstract: Building the infrastructure for Smart technologies, systems and services with the aim of creating a center of excellence in the subject research. The task of the project is to increase the quality of top research workplaces and research-educational workplaces in the subject area of research, taking into account the strategic importance of these areas for the development of the economy and society.
Center of Excellence for SMART Technologies, Systems and Services II
Annotation: Completing the infrastructure for the Center of Excellence in SMART technologies, systems and services.
Interoperability support for SMEs based on ISU (Commius-APVV)
COMMunity-based Interoperability Utility for SMEs
Annotation: Co-financing of RD activities of the relevant 7RP project up to a maximum of 25% of the RD activity budget. In the 2010 report, we report this project only as another financial source of the relevant 7RP project, even though the contract with APVV is signed until 31.01.2011.
ISU-based Interoperability Support for SMEs (Commius-MVTS)
COMMunity-based Interoperability Utility for SMEs
Annotation: Support mainly to cover non-claimable expenses such as VAT expenses of the relevant 7RP project and to improve especially travel expenses. The new MVTS rules valid since 2010 do not allow financing this project, even if the MVTS contract is valid until 31.01.2011.
Advanced Data Mining and Integration for Europe (ADMIRE-APVV)
Advanced Data Mining and Integration Research for Europe
Annotation: Additional financing of RD activities of the relevant 7RP project up to a maximum of 25% of the RD activity budget. In the report for 2010, we report this project only as another financial source of the relevant 7RP project, even though the contract with APVV is signed until 28.02.2011.
Advanced Data Mining and Integration for Europe (ADMIRE-MVTS)
Advanced Data Mining and Integration Research for Europe
Annotation: Support mainly to cover non-claimable expenses such as VAT expenses of the relevant 7RP project and to improve especially travel expenses. The new MVTS rules valid since 2010 no longer allow financing this project, even if the MVTS contract is valid until 28.02.2011.
Prediction and detection methods of significant and dangerous phenomena based on meteorological data mining
Data Mining Meteo (DMM)
Annotation: The subject of the solution is research into parametrizable prediction models and detection methods of significant and dangerous meteorological phenomena (rainfall, fog, low cloud cover). Intense precipitation detected by radar – danger of flooding, current and localized forecast of fog with visibility below 500 m and 200 m – danger to road and air transport , the amount of low clouds covering more than 4/8 of the sky – limiting the landing of aircraft. The prediction of the beginning and end of fog means a contribution to air traffic planning by airport dispatchers and national, regional and international air traffic control centers. Detection and forecasting methods are based on statistical-climatic methods combined with knowledge discovery – mining (“data mining”) of meteorological data (SYNOP reports, METAR , radar images and their sequences, data from measuring stations, satellite images, forecasts of common LAM meteorological models).
Industry research in the area of effective work with large data in user-oriented applications (RECLER)
Abstract: The topic of ergonomics and work efficiency of computer users has recently increasingly become one of the key aspects of the development of applications for information and communication technologies. It is one of the supporting areas of research within the broader discipline, which is usually referred to as human-computer interaction (Human-Computer Interaction, or HCI). largely based on relational database systems (RDBMS), which provide a number of advantages: robustness, scalability, flexibility, performance. However, the situation is changing, and with the increasing number of applications and the volume of managed data, one of the requirements is coming to the fore: scalability. Relational databases are scalable if scaling takes place vertically on a single node (server). Once the capacity of a given node is exceeded and there is a need for horizontal scaling and distribution of data across multiple nodes, the complexity of the configuration will exceed the overall benefit obtained from the increase in capacity. Innovative approaches that are the subject of this research emphasize consistency, accessibility and scalability (CAP – Consistency, Availability, Partitiontolerance).
Service-based distributed computing and data management
Abstract: Service-oriented architectures and software services, as their basic building blocks, are one of the most important research paradigms of current distributed information systems. There is a need for new approaches and methods that would allow working with the knowledge that will be available in the future service-oriented environment. In this environment, the convergence between existing grid technologies, web services, semantic technologies and service-oriented architectures will enable the advanced provision of computation, data, information and knowledge potential. The project focuses on selected topics, which are the use of semantics in a service-oriented environment, the deployment of services in the Grid, services for data management and the visualization of service-oriented scientific calculations in the Grid. At the same time, the project aims to verify the investigated approaches on the application of using a service-based grid system to reduce the dimension of the classification space, as well as on other selected applications.
Slovak infrastructure for high performance computing (SIVVP)
Annotation: The national project SIVVP aims to build a computer infrastructure that will enable the implementation of high-performance calculations for science, research, development and the academic sphere at the European level. The realization of this goal will make available the computing infrastructure for the needs of research and development organizations as well as universities throughout Slovakia . A qualitatively new level of high-performance computing technology and its availability ensured through the SANET network from all relevant workplaces will create prerequisites for equal participation in the European research area. This national project from the closed call OPVaV/K/RKZ/NP/2009-1 has 2 mirror parts (for the regions and for Bratislava).
Enabling Grids for E-scienE III (EGEE-III-MVTS)
Annotation: Support mainly to cover non-claimable expenses such as VAT expenses of the relevant 7RP project and to improve especially travel expenses. In the report for 2010 we report this project only as another financial source of the relevant 7RP project, even though the MVSTS contract continued until 30.4.2010.
Sports Video And Statics Automation System (SVASAS)
Annotation: The implementation of the main project activities Industrial Research and Experimental Development will enable the creation of a new software product with extensive possibilities of use in the field of automating live video transmissions from sports events and automating the generation of statistical information. The product will be based on software solutions and will be easy to deploy. The project was terminated prematurely, the original end of the solution was 30.11.2022.
Urgent Computing for Exascale Data (U-COMP)
Abstract: The current challenges of the European ICT research area emphasize the integration of research infrastructures, transition to services, open access to data and re-use of services, data and research results. In addition, European infrastructures are now moving towards big data processing and exascale data, using new forms of HPC such as emergent computing. The ability to use exascale systems to provide critical support for urgent computing depends on the ability of supercomputing centers to provide urgent computing as a new mode of computing. Urgent computing must be a service provided by future European research computing centers. This will have the dual benefit of providing the societal benefits of the best performing systems and the acquired ability to optimize the design of future operations centers to support urgent computing. These challenges are best addressed by merging web, semantic web technologies to simplify data retrieval, and cloud computing as a flexible platform for e – services. We would like to help better understand the challenges of e-service composition and orchestration as we execute them at scale, and enable e-service operators and users to truly enter the era of cloud computing by providing a methodology, architecture, tools and standards that facilitate and make more secure and cheaper true cloud applications and distributed service-oriented applications. Therefore, we have chosen four areas of research that we want to focus on in this proposal: • composition and orchestration of processes composed of electronic services, supporting the paradigm of urgent computing; • use of semantic web technologies in describing services and domain components of processes; • interoperability of cloud environments and HPC resources and their use in urgent computing; • scalable and distributed data aggregation and analysis.
Research and development of new information technologies for predicting and solving crisis situations and the safety of the population (CRISIS)
Abstract: The safety of the population, anticipation of natural disasters and crisis management are among the current topics in society. The development of IT enables the application of sophisticated methods in an effort to reduce threats to the population, property and the environment. By implementing project activities, a synergistic effect will be achieved, which will strengthen the ability of all application outputs to be applied in practice. The individual activities of the project are interconnected with the aim of integrating the research results into a broadly conceived security system, the applicability of which will be in several areas of protection of the population, property and the environment. The benefit of the project will be the enrichment of research in individual areas with additional aspects that will increase the added value of the resulting solution. The advantage of a comprehensive approach to the IS solution for security is also the part of research in the field of development of progressive technologies for the preparation of special circuits and sensors for IS. The transferability of the results to practice will be improved by adding such features of safety systems as the use of expressive speech synthesis to generate emotionally colored warnings, the creation of visualization tools for simulating the spread of fires, visualization of speech synthesis and interconnected mechatronic systems that will ensure the monitoring of moving objects, the detection of risky situations and to smart mobile mechatronic systems for ensuring movement in risky terrain.
Research on the application of artificial intelligence tools in the analysis and classification of hyperspectral sensing data (HYSPED)
Annotation: The project “Research on the application of artificial intelligence tools in the analysis and classification of hyperspectral imaging data” within the framework of effective cooperation combines independent research and development activities provided by the Technical University in Zvolen and the Institute of Informatics of the Slovak Academy of Sciences, with industrial research provided by the company VUJE, a.s. As part of the project, engineering, research and development work will be carried out, including the implementation of repeated aerial photography of selected sections of power lines, using the top technology of individual partners. Research excellence is supported not only by a top team, which includes 4 guarantors from different fields, but also by the project’s focus on current research trends, which it brings together for the needs of applications in the field of energy in the Slovak Republic. The goal of the project is to use artificial intelligence methods to create models for the detection and classification of tree species, using hyperspectral images and data obtained by LiDAR technology as part of aerial photography of power line structures. The most important output of the project will be a validated model with the support of cloud infrastructure for the detection and classification of objects of interest at the TRL 5 level, which can be exceptional even on a global scale. The outputs of the project will also be a geodatabase of reference tree characteristics, a library of spectral curves, a database of tree growth simulation, as well as a cloud infrastructure to support the development of classification models and data storage. The results of the project will have an impact on the way of performing aerial scanning of line constructions, and their application will bring a higher quality of the implementation of this service in practice. The high quality of outputs will also be reflected in the dissemination of results, as well as in publishing activities. The implementation of the project will also contribute to the increase in the number of registered intellectual property rights due to the implementation of research activities in the Slovak Republic. (Operational Program Integrated Infrastructure)
Research of technologies for management of business processes in heterogeneous distributed systems in real time with the support of multimodal communication (RPKOM)
Abstract: Research of technologies for management of business processes in heterogeneous distributed systems in real time with the support of multimodal communication. Center for research of technologies for management of business processes in heterogeneous distributed systems in real time with the support of multimodal communication. Research of knowledge technologies for management of business processes. Investigation and design of multimodal communication optimizations.
PFO-CAD CP93: 7896 – Copernicus program – Geometric Modeling for CIM-oriented Virtual Reality
Annotation: Geometric Modeling for CIM-oriented Virtual Reality – PFO-CAD CP93: 7896
The responsible researcher for the Institute of Control Theory and Robotics of the SAS was Doc. RNDr. Jaroslav Fogel, CSc.;
J. Sebestyénová entered information about the project into the ELVYS system; co-investigators of the project from UTRR SAS (attached to the Institute of Informatics since 2004) were: J. Fogel, P. Kurdel, K. Dobrovodský, J. Sebestyénová
CSG Modeling is part of almost all CAD-systems for the modeling of solid state matter. Numerous theoretical investigations and implementations have been carried out. Besides its advantages, CGS models still need to be modified into envelope representations for many applications. Parametrizing and real time capabilities are getting lost by this process.
European links: The project will run in strict conjunction with CP93-9554 DODECAS
The Modeling will be made capable of real time by focusing on a subset of CSG Models. Generic storage in databases will be established by using appropriate canonization of representations. Deductive retrieval of variants will be substantially eased.
The name of the partial task solved by the team from our institute: Fast matching algorithm for protein graphs.