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University of Oulu

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5 Projects, page 1 of 1
  • Open Access mandate for Publications
    Funder: FCT Project Code: PD/BD/132407/2017
    Funder Contribution: 63,979.4 EUR
    Partners: FCUP/UP, University of Oulu
  • Funder: ANR Project Code: ANR-16-WTW5-0002
    Funder Contribution: 807,659 EUR
    Partners: Swedish University of Agriculture, University of Oulu, UBC

    Source streams, or headwaters, are often provided with the least protection from forestry and other land uses. However, the impact on ecological status of small streams from increasing water temperature, mobilising sediment, nutrients and contaminants may overwhelm the resilience of these stream ecosystems. Moreover, such changes initiate the downstream transport of these altered conditions. Protection of source streams by providing sufficient buffers is considered to be costly, but that is primarily as opportunity costs for industry. When the values of ecosystem services to downstream users is included, there is a potentially different solution. This is critical to fulfilling the Water Framework Directive 7 (and similar goals for protection of water in Canada and other countries) to ensure that anthropogenic alterations do not impair the ecological status of streams, or their inputs to downstream rivers and lakes. Source streams with small catchment areas are also prone to extreme events, both droughts and floods, relevant to the Floods Directive. Moreover, climate-proofing our stream networks through riparian area protection to reduce uncertainty about water supplies and downstream impacts may provide additional values to aid in sorting out the trade-offs among benefits (relevant to Horizon 2020). This project aims to estimate the ecological, hydrological, water quality, and economic consequences of different management scenarios (e.g., buffers), by comparing the economic and social trade-offs for different value sets and management practices, and to reduce uncertainty of how these possible impacts integrate across scales. We have three objectives. First, we will develop a model platform to explore the consequences of various forms of streamside management around source (headwater) streams. This model will use existing and new data on nutrient flows, sediment fluxes, temperature increases, and loss of productive capacity under different forest management treatments and across many landscapes. The opportunity costs of foregone timber extraction will be compared against the trade-offs to other ecosystem values (clean water, flood protection, productivity). We will generate scenarios of different management configurations to be explored by policy-makers. This will enable a discussion of the value of better protecting source streams and perhaps giving up some protection to larger streams to meet Water Framework Directive objectives. Our second objective is to augment the available data for small stream responses to forest management across our varied landscapes, using comparisons of harvested versus unharvested (no recent harvests) with and without riparian reserves, and to compare headwater versus larger streams. This will be coupled with mesocosm-scale experiments to determine mechanisms of responses by small streams to forestry impacts. Our third objective is to prepare a design and white paper for the large, distributed, landscape-scale experiment that should be done to determine the ecosystem values gained by protection of headwater streams.

  • Funder: ANR Project Code: ANR-19-CHR3-0007
    Funder Contribution: 318,555 EUR
    Partners: HUAWEI TECHNOLOGIES FRANCE, StreamOwl, Athens University of Economics and Business - Research Center, Universitat Politècnica de Catalunya, EURECOM, University of Oulu

    The LeadingEdge project will deliver a novel and holistic framework to efficiently cope with unresolved challenges in edge computing ecosystems, regarding dynamic resource provisioning to multiple coexisting services amidst unknown service- and system-level dynamics. The project approach is three-faceted; it will optimize intra-service resource provisioning, inter-service resource coordination, and user perceived quality of experience (QoE). First, at service level, we will develop a framework, grounded on first principles, for opportunistic use of edge and cloud computation, bandwidth and cache resources according to instantaneous resource availability, mobility, connectivity, service resource requirements and service demand. Our approach will rely on solid online-learning theories such as online convex optimization (OCO), and transfer learning and it will eliminate our inherent inability to predict demand, mobility, and other dynamic processes that affect resource allocation. It will also use extreme-value theory and stochastic optimization towards a full-fledged study of the latency-reliability trade-off that is fundamental for mission-critical services. Proof-of-concept (PoC) validation will be provided through, (i) a real-time image recognition tool as part of a video analytics procedure, (ii) two alternative video quality assessment solutions with different degree of complexity and different configurations of edge/client or cloud resources. After service-level optimization, at a second level, we will develop a system-level AI-empowered service orchestrator based on reinforcement learning and context awareness for service orchestration in terms of network slicing and service chain placement, such that instantaneous service-level requirements are fulfilled. The (OAI) and software platforms will be used as real-time experimentation environments with full 4G/5G functionalities for service orchestration to place services, direct traffic from users to servers, and measure latency and other QoE metrics. Finally, at user level, we will leverage the community-network infrastructure of as an edge network to deploy services at scale in a controlled manner and to directly measure their impact on user QoE. The outcome of these latter user-level studies will be continually fed back to and guide the service- and the system-level optimization. The project results are envisioned to be transformational for edge computing and to create durable impact through enabling game-changing services. This ambitious objective will be pursued with a balanced consortium of complementary expertise, consisting of 3 universities, a research centre, a SME, and a large industry, overall spanning 4 countries.

  • Funder: ANR Project Code: ANR-16-WTW5-0003
    Funder Contribution: 281,215 EUR
    Partners: BUREAU DE RECHERCHES GEOLOGIQUES ET MINIERES - BRGM, G.E.O.S. Ingenieurgesellschaft mbH, ADERA, Kungliga Tekniska Högskolan, University of Oulu, Geologian tutkimuskeskus

    Arsenic in agricultural soils and water, and its subsequent entering into the food chain cause potential risk to human health and to aquatic and soil organisms. AgriAs addresses the global problem of water and soil pollution by arsenic from multidisciplinary perspective and highlights the needs of sustainable development and healthy food chain. The main objective of AgriAs is to evaluate and manage European risks of As exposure through agriculture, providing a complete summary of efficient tools available for As remediation as well as an array of tools for ecotoxicity evaluation that will help stakeholders and decision makers to manage As contamination. In order to accomplish this, the project will build on existing knowledge by using comprehensive national and European databases, developing and testing new technologies and carries out risk monitoring. Particular attention will be paid to demonstration and dissemination of project deliverables in close interaction with stakeholders, end-users and policy-makers. The project team has a wide international network and numerous international projects on-going for arsenic studies. The results of the project have potential for commercial exploitation and new job creation especially in water and soil treatment. The results and the new knowledge can be utilized also by the SMEs, especially in the generation of bio-indicators, new fertilizers and soil-conditioners. This research proposal complements the strategic priorities in Water RDI, such as sustainable ecosystems, safe water for citizens, and water-wise bioeconomy.

  • Funder: ANR Project Code: ANR-19-MRS1-0002
    Funder Contribution: 29,916 EUR
    Partners: ARISTOTLE University of Thessaloniki, CENTRE EMILE DURKHEIM, University of the Basque Country, Bucharest University, University Lodz, RUHR UNIVERSITY BOCHUM, University of Oulu, University of Umea, Università di Torino, UNIVERSITY OF PORTO

    For ten years, the European Union considers the notion of gender equality through the lens of a liberal political mindset, aiming to rally an entire highly-skilled workforce to maintain the continent’s economic competitiveness internationally. Research and academia are at the same time dramatically evolving through the generalisation of competitive funding and the establishment of excellence policies. Observing that in this context, female researchers remain underrepresented, the RESET project (Rethinking gender Equality and Scientific Excellence Together) aims to address the following question: how, and to which extent, do scientific excellence norms have an impact on female researcher’s careers, with regard to the local academic and national labour markets? Supported by Equal Opportunities Officers from several European universities, most of whom are researchers involved in Social Sciences and Humanities, RESET brings research and political action together. It intends to make the most out of its practical and organisational dimension to address research areas currently ignored by SSH research on the obstacles to women’s career progression in academia. European literature traditionally analyses women’s position in academic careers in three categories: at micro (individuals), meso (organisations) or macro level (society) (Lefeuvre 2016). Corrective actions that form the GEP tie these three dimensions together. Through the questions we raise and the data we collect, the project intends firstly to provide answers to the “grey area” of comparative analysis at a European level identified by Nicky Lefeuvre. In the context of RESET, mechanisms of women’s inclusion/exclusion in scientific careers with regard to the national academic labour market will be compared on four criteria: duration and status of the granting of tenure after the PhD, methods of selection for professorial positions, distribution of positions between “local” and “national” candidates, decisions related to the allocation of resources (salaries). Beyond the use of qualitative and quantitative methods of survey, the definition and implementation of the GEPs shall collect information of the effects of the norm of scientific excellence on the gender of academic careers, depending on the state of the academic labour market for each university and of each national context. The guideline of the corrective actions of the GEPs is to act upon the academic career continuum (PhD enrolment, allocation of a tenured position, access to senior/higher positions; emeritus, honours and academic acknowledgements). The second major research guiding principle of the RESET project will consist in addressing the impact of the international norm of scientific excellence on gender-related career inequalities among the partner European universities. The most common analytical frame used to describe the evolution of the higher education and research landscape is the new public management (Musselin 2017). In an operational perspective, the implementation will be closest to the laboratories and involving its members and directions. It relies on interviews, which approach is twofold: practice- and research-oriented.