Project
Institute of Informatics
International Projects
iMagine - Imaging data and services for aquatic science (iMagine)
Cloudové služby pre spracovanie obrazových údajov pre vedy o vode
| Duration: | 1. 9. 2022 - 31. 8. 2025 |
| Evidence number: | 101058625 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | iMagine provides a portfolio of free at the point of use image datasets, high-performance image analysis tools empowered with Artificial Intelligence (AI), and Best Practice documents for scientific image analysis. These services and materials enable better and more efficient processing and analysis of imaging data in marine and freshwater research, accelerating our scientific insights about processes and measures relevant for healthy oceans, seas, coastal and inland waters. By building on the computing platform of the European Open Science Cloud (EOSC) the project delivers a generic framework for AI model development, training, and deployment, which can be adopted by researchers for refining their AI-based applications for water pollution mitigation, biodiversity and ecosystem studies, climate change analysis and beach monitoring, but also for developing and optimising other AI-based applications in this field. The iMagine compute layer consists of providers from the pan-European EGI federation infrastructure, collectively offering over 132,000 GPU-hours, 6,000,000 CPU-hours and 1500 TB-month for image hosting and processing. The iMagine AI framework offers neural networks, parallel post-processing of very large data, and analysis of massive online data streams in distributed environments. 13 RIs will share over 9 million images and 8 AI-powered applications through the framework. Having representatives so many RIs and IT experts, developing a portfolio of eye-catching image processing services together will also give rise to Best Practices. The synergies between aquatic use cases will lead to common solutions in data management, quality control, performance, integration, provenance, and FAIRness, contributing to harmonisation across RIs and providing input for the iMagine Best Practice guidelines. The project results will be integrated into and will bring important contributions from RIs and e-infrastructures to EOSC and AI4EU. |
EOSC Beyond - EOSC Beyond: advancing innovation and collaboration for research
EOSC Beyond: pokrok v inováciách a spolupráci v oblasti výskumu
| Duration: | 1. 4. 2024 - 31. 3. 2027 |
| Evidence number: | 101131875 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | EOSC Beyond overall objective is to advance Open Science and innovation in research in the context of the European Open Science Cloud (EOSC) by providing new EOSC Core capabilities allowing scientific applications to find, compose and access multiple Open Science resources and offer them as integrated capabilities to researchers. To do so, EOSC Beyond supports a new concept of EOSC: a federated and integrated network of Nodes operated at different levels, national, regional, international and thematic, to serve the specific scientific missions of their stakeholders. Further specific objectives of the project are to accelerate ‘time to product’ of new scientific applications with software adapters, enable Open Science with machine composability and dynamic deployment of shared resources, support innovation in EOSC with a testing and integration environment, and align the EOSC Core architecture and specifications to integrate with European dataspaces. The project extends the state of the art of the EOSC Core and adopts a co-design methodology, including requirements elicitation, software development and validation in collaboration with different use cases from EOSC national and regional initiatives (e-Infra CZ, Czechia, NFDI, Germany, and NI4OS, South East Europe region), thematic research infrastructures from Social Sciences and Humanities (CESSDA), Life Sciences (CNB-CSIC and Instruct-ERIC), Environmental Science (ENES and LifeWatch), and Health and Food (METROFood-RI). EOSC Beyond builds on the capacities of prospective EOSC Nodes and partners with multi-annual experience in developing solutions for large-scale federated digital infrastructures and aligns with the technical architecture and requirements of data spaces from different business sectors. Ultimately, EOSC Beyond supports Open Science in modern, data-intensive, and multidisciplinary research, facilitating resource discovery, access, and reuse across scientific communities, organisations, and countries. |
NERO - European network on extreme fire behavior (NERO)
Európska sieť pre extrémne správanie požiarov
| Duration: | 17. 10. 2023 - 16. 10. 2027 |
| Evidence number: | CA22164 |
| Program: | COST |
| Project leader: | RNDr. Glasa Ján CSc. |
| Project web page: | https://www.cost.eu/actions/CA22164/#tabs+Name:Description |
Chemiresistive sensors based on 2D nanomaterials
Chemorezistorové senzory na báze 2D nanomateriálov
| Duration: | 1. 1. 2025 - 31. 12. 2026 |
| Evidence number: | Mobilita SAS-BAS-2025-2026 |
| Program: | Mobility |
| Project leader: | Ing. Mgr. Andok Robert PhD. |
| Annotation: | This project proposal builds on the previous project BAS-SAS-2022-05, which focused on investigating new progressive nanostructured 2D materials based on dichalcogenides of transition metals. In this project, we propose to focus on graphene as a 2D material for developing chemiresistive sensors. The subject of this project proposal is research concerning the preparation methods of nanometer patterns in 2D graphene using electron beam lithography, one of the alternative methods for creating nanometer patterns. An important part of the project is addressing the problems associated with the interaction of the electron beam in a very thin electron beam resist (10 - 50 nm) on 2D materials, including graphene. We will conduct experimental examinations and simulations of lithographic parameters on very thin electron beam resists on 2D graphene. We expect to observe new scattering effects that need to be analyzed and clarified in the case of low-energy secondary electrons. Additionally, the scattering of backscattered electrons, which involves long-range electron scattering in the substrate, will be examined. |
BattPor - Inline evaluation of Li-ion batery electrod porosity using machine learning algorithms
Inline evaluácia pórovitosti elektród Li-ion batérií pomocou algoritmov strojového učenia
| Duration: | 1. 6. 2022 - 31. 5. 2025 |
| Evidence number: | M.ERA-NET 3/2021/295/BattPor |
| Program: | ERANET |
| Project leader: | Ing. Malík Peter PhD. |
SILVANUS - Integrated Technological and Information Platformfor wildfire Management (SILVANUS)
Integrovaná technologická a informačná platforma pre manažment lesných požiarov
| Duration: | 1. 10. 2021 - 31. 3. 2025 |
| Evidence number: | H2020-101037247 |
| Program: | Horizont 2020 |
| Project leader: | Ing. Balogh Zoltán PhD. |
| Annotation: | SILVANUS envisages to deliver an environmentally sustainable and climate resilient forest management platform through innovative capabilities to prevent and combat against the ignition and spread of forest fires. The platform will cater to the demands of efficient resource utilisation and provide protection against threats of wildfires encountered globally. The project will establish synergies between (i) environmental; (ii) technology and (iii) social science experts for enhancing the ability of regional and national authorities to monitor forest resources, evaluate biodiversity, generate more accurate fire risk indicators and promote safety regulations among citizens through awareness campaigns. The novelty of SILVANUS lies in the development and integration of advanced semantic technologies to systematically formalise the knowledge of forest administration and resource utilisation. Additionally, the platform will integrate a big-data processing framework capable of analysing heterogeneous data sources including earth observation resources, climate models and weather data, continuous on-board computation of multi-spectral video streams. Also, the project integrates a series of sensor and actuator technologies using innovative wireless communication infrastructure through the coordination of aerial vehicles and ground robots. The technological platform will be complemented with the integration of resilience models, and the results of environmental and ecological studies carried out for the assessment of fire risk indicators based on continuous surveys of forest regions. The surveys are designed to take into consideration the expertise and experience of frontline fire fighter organisations who collectively provide support for 47,504x104 sq. meters of forest area within Europe and across international communities. The project innovation will be validated through 11 pilot demonstrations across Europe and internationally using a two sprint cycle. |
SWORD - Smart Wound monitoring Restorative Dressings
Inteligentné diagnosticko-terapeutické náplasti
| Duration: | 1. 1. 2020 - 30. 6. 2025 |
| Evidence number: | H2020-873123 |
| Program: | Horizont 2020 |
| Project leader: | RNDr. Bardošová Mária CSc. |
| Annotation: | The project aims to combine the expertise and resources of four academic groups working at the frontiers of material research and two SMEs, one engaged in producing commercial medical materials as well as having own research capacities. The Consortium plans to develop wound dressings which an be rated as a radical innovation in the area of chronic wound care. Our efforts will concentrate on the design of a new product which will combine diagnostic and therapeutic actions and facilitate wound healing, while at the same time minimize treatment costs and optimize wound management thus positively influencing patient's wellbeing. A range of new composites derived from naturally occurring materials, such as chitin and halloysite combined with colloids will be studied. The ensuing hybrid materials will be processed using micro- and nano-manipulating tools, including roll-to-roll and electrospinning technologies. A thorough characterization program will be undertaken in order to understand the molecular-level interactions between the composite components. The determination of materials structure will allow a complete understanding of how their properties originate so that they can be tailored to precisely fit their application. The dressing will feature diagnostic sensors capable of measuring pH, humidity, temperature and associated bacterial activity as well as a highly absorbent layer designed to drain the wound and release therapeutic agents. Each member of the Consortium is well-resourced in terms of facilities, infrastructure and technology transfer support so as to provide an ideal environment for the research program, the training of younger researchers and the exploitation of findings. Leveraging from nationally funded grants and actively engaging in research exchanges while seeking to produce a radical innovation in the area of 'smart' dressings the project will address all three key drivers of the knowledge-based society, namely research, education an innovation. |
| Project web page: | https://cordis.europa.eu/project/id/873123 |
AI4EOSC - Artificial Intelligence for the European Open Science Cloud (AI4EOSC)
Umelá inteligencia pre EOSC
| Duration: | 1. 9. 2022 - 31. 8. 2025 |
| Evidence number: | 101058593 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | The AI4EOSC (Artificial Intelligence for the European Open Science Cloud) delivers an enhanced set of advanced services for the development of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) models and applications in the European Open Science Cloud (EOSC). These services are bundled together into a comprehensive platform providing advanced features such as distributed, federated and split learning; novel provenance metadata for AI/ML/DL models; event-driven data processing services or provisioning of AI/ML/DL services based on serverless computing. The project builds on top of the DEEP-Hybrid-DataCloud outcomes and the EOSC compute platform and services in order to provide this specialized compute platform. Moreover, AI4EOSC offers customization components in order to provide tailor made deployments of the platform, adapting to the evolving user needs. The main outcomes of the AI4EOSC project will be a measurable increase of the number of advanced, high level, customizable services available through the EOSC portal, serving as a catalyst for researchers, facilitating the collaboration, easing access to high-end pan-European resources and reducing the time to results; paired with concrete contributions to the EOSC exploitation perspective, creating a new channel to support the build-up of the EOSC Artificial Intelligence and Machine Learning community of practice. |
| Project web page: | https://ai4eosc.eu/ |
EuroScienceGatew - leveraging the European compute infrastructures for data-intensive research guided by FAIR principles (EuroScienceGateway)
využitie európskych výpočtových infraštruktúr pre výskum náročný na údaje riadený zásadami FAIR
| Duration: | 1. 9. 2022 - 31. 8. 2025 |
| Evidence number: | 101057388 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | In the past decade, many scientific domains have been transformed into data-driven disciplines relying on the exchange and integration of internationally distributed data. Exploiting this data is still a laborious and largely manual task, prone to losses and errors, and increasingly specialised beyond most users technical capabilities. FAIR practices are encouraged but their adoption curve is steep. The needs for compute and data resources, tools, and application platforms are often domain-specific. Many scientists struggle to navigate this intricate ecosystem. Generally, researchers do not possess the computing skills to effectively use the HPC or Cloud platforms they need. Thus, new approaches are needed to enable all researchers, with widely ranging digital skills, to efficiently use the diverse computational infrastructures available across Europe, for asynchronous and for interactive applications. EuroScienceGateway will leverage a distributed computing network across 13 European countries, accessible via 6 national, user-friendly web portals, facilitating access to compute and storage infrastructures across Europe as well as to data, tools, workflows and services that can be customized to suit researchers' needs. At the heart of the proposal workflows will integrate with the EOSC-Core. Adoption, development and implementation of technologies to interoperate across services, will allow researchers to produce high-quality FAIR data, available to all in EOSC. Communities across disciplines - Life Sciences, Climate and Biodiversity, Astrophysics, Materials science - will demonstrate the bridge from EOSC's technical services to scientific analysis. EuroScienceGateway will deliver a robust, scalable, seamlessly integrated open infrastructure for data-driven research, contributing an innovative and customizable service for EOSC that enables operational open and FAIR data and data processing, empowering European researchers to embrace the new digital age of science. |
SIESTA - Secure Interactive Environments for SensiTive data Analytics (SIESTA)
Zabezpečené interaktívne prostredia pre analýzu citlivých údajov
| Duration: | 1. 1. 2024 - 31. 12. 2026 |
| Evidence number: | 101131957 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | The FAIR principles provide a framework for enabling proper access and reusability of scientific data, and implementing them is a key goal of the European Open Science Cloud (EOSC). However, providing access to sensitive or confidential data while preserving privacy/confidentiality and usability for researchers is still an open question. Existing solutions like safe rooms, safe pods, or data safe havens are often challenging for the development of reproducible research and seem counter-intuitive when dealing with open science and FAIR principles. The SIESTA project aims to provide a set of tools, services, and methodologies for the effective sharing of sensitive data in the EOSC, following a cloud-based model and approach. SIESTA will provide user-friendly tools with the aim of fostering the uptake of sensitive data sharing and processing in the EOSC. The project will deliver trusted cloud-based environments for the management and sharing of sensitive data that are built in a reproducible way, together with a set of services and tools to ease the secure sharing of sensitive data in the EOSC through state-of-the-art anonymization techniques. The overall objective is to enhance the EOSC Exchange services by delivering a set of cloud-based trusted environments for the analysis of sensitive data in the EOSC demonstrating the feasibility of the FAIR principles over them. |
National Projects
AI4CC - AI-Driven Self-awareness and Cognition for Compute Continuum (AI4CC)
Adaptívna a reflexívna umelá inteligencia pre výpočtové kontinuum
| Duration: | 1. 7. 2024 - 30. 6. 2027 |
| Evidence number: | APVV-23-0430 |
| Program: | APVV |
| Project leader: | doc. Ing. Hluchý Ladislav CSc. |
| Annotation: | AI4CC aims to contribute with new AI-based methods and algorithms to the development of modern computing continuums, addressing some of the key challenges of this domain. These challenges include enhancing the autonomy and self-adaptation capabilities of compute continuum platforms to optimize decision-making and responsiveness; adapting to changing conditions, necessitating flexible and adaptive computing models for dynamicity; efficiently managing vast amounts of data, considering factors like decentralization, scalability, and real-time processing for effective Data Management; ensuring transparency, explainability, and accountability in AI and machine learning models within compute continuums; achieving seamless interoperability between diverse devices and platforms within the continuum, impacting data exchange and communication for Interoperability, and dealing with resource heterogeneity—variability in computing resources across the continuum, including edge and cloud environments, posing challenges in optimizing performance and resource utilization. By systematically addressing these challenges and pioneering advancements in these key areas, AI4CC aims not only to bridge existing gaps but to propel compute continuums into a new era of efficiency, adaptability and security. The project envisions a future where compute continuums seamlessly integrate into various domains, fostering a holistic and intelligent computing environment that adapts to the ever-evolving demands of the digital landscape. |
ALOIS - Diagnosis of Alzheimer's disease from speech using artificial intelligence and social robotics
Diagnostika Alzheimerovej choroby z reči s použitím umelej inteligencie a sociálnej robotiky
| Duration: | 1. 7. 2022 - 30. 6. 2025 |
| Evidence number: | APVV-21-0373 |
| Program: | APVV |
| Project leader: | Ing. Rusko Milan PhD. |
EnviroSens - Environmental sensors based on 2D nanomaterials
Environmentálne senzory na báze 2D nanomateriálov
| Duration: | 1. 8. 2024 - 31. 7. 2026 |
| Evidence number: | SK-BG-23-0017 |
| Program: | APVV |
| Project leader: | RNDr. Kostič Ivan |
| Annotation: | The objective of this project proposal is the research of new semiconducting 2D materials for application in environmental sensors. 2-dimensional (2D) materials have been at the forefront of materials research in recent years due to their unic electrical and optical properties and interesting mechanical properties deriving from their atomically thin dimensions. One of promising applications of 2D materials are chemical, environmental, and biological sensor devices based on such 2D materials. In this project, we will focus on the development of environmental sensors based on 2D materials with concentration on gas sensors. |
| Project web page: | https://www.ui.sav.sk/w/odd/senzor/projekty/ |
BioStimul - Experimental System for Wireless Stimulation and Monitoring of Selected Biological Properties and Cognitive Abilities of Drosophila melanogaster.
Experimentálny systém pre bezkontaktnú stimuláciu a monitorovanie vybraných biologických vlastností a kognitívnych schopností Drosophila melanogaster.
| Duration: | 1. 9. 2024 - 30. 6. 2027 |
| Evidence number: | APVV-23-0173 |
| Program: | APVV |
| Project leader: | Ing. Mgr. Andok Robert PhD. |
| Annotation: | The fruit fly Drosophila melanogaster serves as one of the most versatile models for studying human diseases, including neurodegenerative or learning disorders. Thanks to the unique genetic tools available exclusively in the fly model, Drosophila considerably contributed to discoveries of genetic regulations behind processes such as learning and behavior. Nevertheless, progress in this research area is limited by available technologies for the stimulation and tracking fruit flies. This project aims to develop novel equipment for wireless stimulation and monitoring of insect behavior. A wireless micro-heater will be installed onto the Drosophila’s body, designed and developed within this project, together with the microsensor of position / force. The fly will be stimulated individually under certain circumstances by locally controlled heat induced in the micro-heater realized by connecting a nanometric diamond film (as a supporting material bilogically compatible with the examined tiny insects, and at the same time a material with excellent thermal conductivity) with a high density micro coil consisting of a closed LC resonant circuit with a high-k dielectric material (ZrO2, SrTiO3, HfO2) used for the micro-capacitor. By exerting electromagnetic waves of certain resonant frequency related to the size of the coil, electromagnetic induction will occur and the device will heat up stimulating the insect. The project aims to optimize and utilize this technology for the study of olfactory and social learning. The technology will nonetheless have a broad impact in other areas of Drosophila neuroscience, ethology and physiology. The system can be, for example, used also for wireless stimulation of flies in various types of learning experiments, for tracking fly behavior in complex environments, or for studies of behavioral roles of diverse genes and environmental factors. The suggested technology will have broad implications in both primary research and biomedicine. |
Intelligent sensor systems and data processing
Inteligentné senzorové systémy a spracovanie dát
| Duration: | 1. 1. 2023 - 31. 12. 2026 |
| Evidence number: | VEGA 2/0135/23 |
| Program: | VEGA |
| Project leader: | Ing. Malík Peter PhD. |
| Annotation: | The central theme of Industry 4.0 and 5.0 is the digitization, intelligence and decentralization of management, so a key research is the new generation of smart sensors, able to cooperate and adapt to environment changes. This will be achieved by researching new methods of aggregating hyperspectral and multimodal data, as well as algorithms using artificial intelligence. The project is focused on intelligent algorithms for non-contact surface sensing in high-noise environments, which are able to learn the nature and noise distribution from data. This results in higher accuracy and greater noise robustness. The emphasis is on the classification and anomaly detection, which will bring more accurate and robust algorithms for use with the high noise content and long-tailed distribution that dominates in the common industrial environment. Research into aggregation algorithms for heterogeneous and multisensor data will bring new compensation mechanisms to suppress the effects of negative factors on sensor systems. |
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Manipulácia, funkcionalizácia, elektrónové vlastnosti a bioaplikácie 2D materiálov: 2D-MAT
| Duration: | 1. 1. 2024 - |
| Evidence number: | 2/0040/24 |
| Program: | VEGA |
| Project leader: | Prof.Ing. Štich Ivan DrSc. |
RFMEMS - Microelectromechanical sensors with radio frequency data transmission
Mikroelektromechanické senzory s rádiofrekvenčnýcm prenosom údajov
| Duration: | 1. 7. 2021 - 30. 6. 2025 |
| Evidence number: | APVV-20-0042 |
| Program: | APVV |
| Project leader: | Ing. Havlík Štefan DrSc. |
| Annotation: | The project elaborates the method proposed by the authors, especially of mechanical quantities with wireless signal / energy transmission via electromagnetic field, solution of sensors as well as (micro) electro-mechanisms (MEMS). The task is a logical continuation of the results achieved within the successful solution of the previous project APVV 14-0076, where the principle of scanning and conception of the sensor solution according to the original design (utility model 8653, published patent applications PP 121-2018) was designed and verified. The presented project represents further theoretical and methodological-experimental processing in order to meet specific requirements for the solution of specific sensors including compliant - deformation members and electronic evaluation circuits as well as other electro-mechanisms with respect to selected applications. Part of the solution is to create tools for modeling, simulation and optimization of properties using available MEMS technologies. The project aims to follow the latest global trend in MEMS solutions. |
| Project web page: | - |
Computer simulation of airflows and fire smoke spread in critical structures
Počítačová simulácia prúdenia vzduchu a šírenia dymu pri požiari v kritických objektoch
| Duration: | 1. 1. 2024 - 31. 12. 2027 |
| Evidence number: | VEGA 2/0096/24 |
| Program: | VEGA |
| Project leader: | Mgr. Weisenpacher Peter PhD. |
| Annotation: | Research in the proposed project is focused on formulation of new scientific knowledge on computer simulation of airflows and fire smoke spread in critical structures. Motorway tunnels were selected as the main subject of research interest based on discussions with specialists on fire safety in Slovakia. Tunnels belong to inteligent structures with high safety requirements due to potentially huge losses in case of fire. Natural airflows, airflows created by emergency ventilation, airflows induced by fire and fire smoke spread will be analyzed with focus on velocity fields, velocity profiles and smoke stratification. Computational aspects of efficient parallel realization of computer simulation on HPC systems will be investigated as well. The previous research results, experience and obtained experimental data will be utilized. The research is in line with current research trends and requirements of the fire researchers’ and simulators developers’ community and has potential to have significant social impact. |
Progressive methods of the transfer of nanostructured semiconductive 2D materials based on transition metal dichalcogenides onto microelectronic elements
Progresívne metódy transferu nanoštruktúrnych polovodivých 2D materiálov na báze dichalkogenidov tranzitných kovov do mikroelektronických prvkov
| Duration: | 1. 1. 2022 - 31. 12. 2025 |
| Evidence number: | 2/0099/22 |
| Program: | VEGA |
| Project leader: | Ing. Mgr. Andok Robert PhD. |
| Annotation: | The aim of this project is to carry out basic research in the field of new progressive nanostruct. semiconductive materials based on dichalcogenides of transition metals with the focus on nanostructured disulfides. The properties of selected nanostructured disulfides will be examined in terms of their use in microlelectronics and expected advantages of nanostructured disulfides in comparison with bulk semiconductor materials will be shown. We will design model microelectronic devices based on specific nanostructured disulfides such as WS2, MoS2, MSe, and develop technological methods for their preparation. We will master mechanical exfoliation of nanostructured disulfide layers and transfer of these nanostructured layers to the microelectronic device on the substrate. We will also focus on the analysis of these layers and their structural properties by physical methods (SEM, AFM, EDX, Raman spectroscopy...) and on the characterization of electrical and transport properties of the model microel. structure. |
Semantic distributed computing continuum for extreme data processing
Sémantické distribuované výpočtové kontinuum pre spracovanie extrémnych dát
| Duration: | 1. 1. 2023 - 31. 12. 2025 |
| Evidence number: | 2/0131/23 |
| Program: | VEGA |
| Project leader: | doc. Ing. Hluchý Ladislav CSc. |
Study of critical airflow velocity in tunnel using Fire Dynamics Simulator
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| Duration: | 17. 10. 2024 - 16. 10. 2025 |
| Evidence number: | p851-24-3 |
| Program: | Iné projekty |
| Project leader: | Ing. Valášek Lukáš PhD. |
2DQMC - -
Štúdium elektrónových vlastností 2D materiálov ultra-presnými metódami kvantového Monte Carla
| Duration: | 1. 7. 2022 - 30. 6. 2025 |
| Evidence number: | APVV-21-0272 |
| Program: | APVV |
| Project leader: | prof. Ing. Štich Ivan DrSc. |
AIPOLOGY - Artificial Intelligence for Personalised Oncology: from Single-Sample Assessment to Real-time Monitoring of Solid Tumours (AIPOLOGY)
Umelá inteligencia pre precíznu onkológiu: od analýzy jednotlivých vzoriek po real-time monitorovanie progresie nádorových ochorení.
| Duration: | 1. 7. 2022 - 30. 6. 2025 |
| Evidence number: | APVV-21-0448 |
| Program: | APVV |
| Project leader: | doc. Ing. Hluchý Ladislav CSc. |
| Annotation: | The methodologies that oncologists use to decide on a patient's treatment are ever changing. It seems to us that 21st century cancer medicine is much about analysing big data and using mathematical modelling to extract information that can help predict how tumours will evolve and react to potential therapies. The sad fact is, however, that despite ever increasing knowledge on cancer we still lack the proper tools to translate this knowledge to an impactful “bedside” practice that would overcome the limitation from cancer heterogeneity and allow real-time monitoring of disease progression. Here, we propose the AIpology project that aims at the development of novel artificial intelligence strategies to identify molecular traits (individual mutations, mutation signatures and genomic scars) in heterogeneous cancer genomes for which therapeutic targets exist. Based on target clonal mapping and ordering, the system will then outline possible courses of treatment and will intelligently adapt as more data from real time monitoring approaches (such as liquid biopsy) will become available. The system will help us to track each target at the finer time scale than it is possible today and predict future (i.e how the tumour will evolve after being treated with a specific drug) and past (i.e. how long the tumour existed prior to detection) cancer evolutionary trajectories from existing data. Finally, we will understand better why certain cancers become (chemo)therapy-resistant and derive clinically relevant recommendations when they do. |
SCDCANS - Stopping criteria to bound distributed consensus algorithms with asymptotic convergence for network size estimation
Zastavovacie kritériá pre ohraničenie distribuovaných konsenzuálnych algoritmov s asymptotickou konvergenciou pre odhad veľkosti siete
| Duration: | 1. 4. 2024 - 31. 12. 2025 |
| Evidence number: | SK-SRB-23-0038 |
| Program: | APVV |
| Project leader: | Ing. Kenyeres Martin PhD. |
| Annotation: | Knowing the network size (or at least its precise estimate) beforehand is crucial for many modern distributed algorithms executed in multi-agent systems. As seen in the literature, widespread consensus-based algorithms for distributed averaging can be easily applicable for this purpose. However, they have not been too frequently used to estimate the network size since their definition. The research of the researchers involved in this project is planned to be focused on how to efficiently stop the execution of these algorithms for network size estimation in a distributed way. The efficient operation of algorithms is one of the most crucial design requirements placed on topical multi-agent systems, as identified in many related manuscripts. The primary goals of this project are to analyze the mentioned algorithms for network size estimation from numerous aspects (e.g., estimation precision, convergence rate, robustness, etc.), examine and optimize the performance of the existing stopping criteria, and to propose novel stopping criteria that optimize consensus-based data aggregation in multi-agent systems. Multiagent systems in this project will be modeled as graphs with random topologies, ensuring a credible representation of real-world systems. An analysis of the used methods' reliability using probabilistic tools such as large deviations is also planned to be done. |
INFOTICK - Getting the right info on ticks (INFOTICK)
Získanie pravdivých informácií o kliešťoch
| Duration: | 1. 7. 2023 - 30. 6. 2027 |
| Evidence number: | APVV-22-0372 |
| Program: | APVV |
| Project leader: | Ing. Gatial Emil PhD. |
| Annotation: | Despite the fact that the castor bean tick, Ixodes ricinus has been studied for a century, many questions regarding its ecology remains unanswered. Several aspects of its basic biology and phenology are still unexplored. Global changes, including climate shifts, transformation of the landscape and urbanization, contribute to the switch not only in tick distribution, but also in bionomics and seasonal activity of ticks. The ornate dog tick, Dermacentor reticulatus adapts quickly to changing conditions and its range is expanding. There is the need for detailed description of areas where these ticks are found (natural as well as urban habitats), since their ranges have changed during the last decades. The main risk factor for tick -exposed people in a given area is the density of infected questing ticks. In the proposed project, questing activity of ticks will be monitored using the tick -plot methodology „tick gardens“ in field plots as well as flagging the vegetation for questing ticks. Using the tick-plot methodology, we will also follow the tick life cycle and the seasonality of various developmental events (especially moulting) as well as the longevity of different life stages. Since these two species of ticks are considered epidemiologically the most important, we will also identify the prevalence and occurrence of both pathogen infected questing ticks and infected ticks feeding on animals. Furthermore, with changing conditions, the invasion and occurrence of „non-native“ species of ticks in Slovakia will be closely monitored since these emerging tick species can introduce new pathogens to our area. The information obtained by the research team during the project as well as during previous studies will be transferred and used in the development of a mobile application for tick identification and the creation of a website that will bring benefits to the general public and professionals to understand the risk of infection with the tick-borne pathogens. |
Projects total: 25