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Reality-Connected Machine Simulation of Heavy Machinery

The RealSim project proposal aims to connect machine simulation to reality in the framework of heavy machinery, which is an interdisciplinary application. The results of this project are expected to optimize machine performance, accurately and reliably predict machine failure, and reduce overall development and operation costs, thus, serving the Europe’s priority of green transformation and the United Nation’s sustainable development goal 9. The RealSim project will close the gaps of: (1) Onboard estimations of force and pressure components of heavy machinery; (2) Estimating deformability, cylinder friction, leakage, and valve dynamics of heavy machinery using independent nonlinear Kalman filters; (3) Employing dependent nonlinear Kalman filters in state estimators of heavy machinery; (4) Tuning algorithms for the covariance matrix of plant noise in the state estimation of heavy machinery. 

I will consolidate and leverage my research career and position as a leading researcher in the field through integration in Assoc. Prof. Mohammad Poursina’s group at the Department of Engineering Sciences of the University of Agder (UiA), Norway. Here, I will acquire hands-on experience of working with actual mechatronic systems and develop efficient control algorithms. I will improve my knowledge of fluid power designing, control theory, instrumentation, and develop efficient coding skills. I will also develop entrepreneurial skills. The skills, knowledge, and international network that I will develop during this fellowship will put me in an excellent position to achieve my long-term goal of becoming a professor with my own independent research group at an esteemed university in EU. This fellowship will help me to prepare a strong ERC Starting Grant application in the future. It will also cater my additional goal of setting-up a research-related start-up in the future.

Algebraic Theory of Information Quantities

Information theory is a discipline at the intersection of statistics, engineering and computer science. As the study of information quantities, such as compression or communication capacities, information content or measures of statistical dependency, it is one of the theoretical underpinnings of data science.

Computational problems in information theory are highly non-linear. The goal of this project is to transfer state-of-the-art methods of computational non-linear algebra to information theory, to study the inherent algebraic complexity of information-theoretical problems and to provide tools for solving them in practice. The algebraic point of view has proven to be fruitful in seemingly unrelated areas, as witnessed by a surge of recent work in algebraic statistics, in particular on likelihood geometry. However, maximizing the likelihood function is the same as minimizing relative entropy — a specific information quantity. Hence, this project also aims at generalizing the techniques developed in likelihood geometry.

One focus is on the practical computation of information quantities using numerical and differential algebraic geometry. Such quantities are defined via non-linear optimization problems and we aim to pinpoint the algebraic complexity of these problems in instances of general interest, such as common information measures. The final objective is finding fundamental laws and limits of data science imposed by non-linear inequalities constraining the entropic region. These inequalities provide, by duality, universal bounds for many of the optimization problems studied in information theory.

WHeelchair Activity Monitoring project (WHAM)

Wheelchair users (WCU) are three to five times more inactive than the general population, leading to a high risk of developing preventable secondary conditions. Although physical activity (PA) guidelines have been specifically developed for WCU, we lack systematic approaches to implement them in practice, as well as valid algorithms to monitor PA change in WCU through sensor-based solutions. Accordingly, the overall scientific aim of the WHeelchair Activity Monitoring project (WHAM) is to advance PA research and practice in WCU by developing valid digital markers for monitoring of and providing feedback on PA, paving the way for implementation and intervention. I will accomplish this through combining the complementary research fields of 1) behavioural intervention studies focusing on increasing PA in WCU (core competence University of British Columbia, UBC; outgoing phase) and 2) sensor-based PA monitoring (core competence Norwegian University of Science and Technology, NTNU; returning phase – consolidated by non-academic placement at Maastricht Instruments, which develop research prototypes including PA monitors). WHAM’s scientific aim is achieved through three objectives: 1) Measure the effect of a pragmatic exercise intervention trial on self-reported physical activity levels and cardio-respiratory fitness, 2) Develop valid algorithms for tracking PA markers in WCU, and 3) Co-create a framework that outlines how PA can be conjointly monitored and provided feedback on in WCU. This fellowship will enable me to become established as an internationally recognized researcher in the field of “physical activity and disability”, while bringing together ongoing national disjointed research activities in this field. Altogether, my overall ambition is to contribute to reducing inequalities in daily-life participation among WCU compared to the rest of the population.

EOSC Beyond: advancing innovation and collaboration for research

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.


Harmonization of Advanced Materials Ecosystems serving strategic Innovation Markets to pave the way to a Digital Materials & Product Passport

The overarching objective of DigiPass is to enhance the digital maturity of the European communities that develop materials and intermediate products. The project will develop recommendations and clear routes toward digitalized circular business models. The overarching key result of DigiPass is to create a sustainable platform which includes support for Digital Materials & Product Passport and for collaborative innovation-by-design processes in a circular economy served by advanced materials. A business model for operating such a platform completes the overarching objective.
DigiPass is harmonizing and synergizing collected materials data sources and digital infrastructures. This will enable interoperability of data exchange, and standardization of advanced materials knowledge representation at all maturity levels. Accelerating the design, development, and production of advanced, safe, and sustainable chemicals and materials, as they are necessary for innovative products, calls for a collaborative approach involving different stakeholders to support durability, repair and overhaul, reuse, and recyclability of products. DigiPass project impacts all materials development communities over the whole circular value chain. 


Enhanced X(cross)-disciplinary Community-driven Imaging Technologies for Earth and Environmental material research

The EXCITE² Network is revolutionizing Earth and environmental material science research by consolidating a critical mass of 18 research facilities in 12 European and associated partner countries into a unified infrastructure and providing transnational access to advanced imaging technologies. This enables scientists to decipher complex processes within Earth materials at scales from nanometres to hundreds of centimetres, gaining unparalleled insight into the chemical and physical processes that govern, among others, environmental toxicity and its impact on human health, critical metal extraction for renewable energies, and the utilisation of Earth materials as long-term storage for climate-altering gases. The consortium fosters knowledge-sharing and talent attraction, bolstering the problem-solving capacity of the European Research Area. Moreover, EXCITE² is driving interdisciplinary collaboration and cross-fertilisation across academic institutions, scientific disciplines, and industry, propelling Europe towards a sustainable future. The initiative offers dedicated training programmes to a new generation of researchers within the European open science landscape, paired with access to world-class imaging facilities and expertise for problem-solving research and innovation. EXCITE² is introducing innovative service developments, such as artificial intelligence and leading-edge imaging experiments, to increase the user's problem-solving capacity. In addition, the consortium is implementing customised project valorisation strategies to maximize the impact of research outcomes in academia, society, and the economy. Citizen science projects allow the public to participate directly within the EXCITE² Network, contributing to solving EU challenges. As such, EXCITE² is paving the way towards a sustainable future, driving scientific excellence, and creating positive societal impact.

NORKLIMA-Klimaendringer og konsekvenser for Norge

On Thin Ice? Climatic influence on Energy Flow and Trophic Structure in Arctic Marine Ecosystems

Tildelt: kr 6,0 mill.

Publikasjoner hentet fra Cristin

Seafloor warm water temperature anomalies impact benthic macrofauna communities of a high-Arctic cold-water fjord

The Sub-Ice Algal Communities of the Barents Sea Pack Ice: Temporal and Spatial Distribution of Biomass and Species

Budsjettformål:

NORKLIMA-Klimaendringer og konsekvenser for Norge

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