• Bokmål
  • English

Nettstedskart

Oversikt over NRs prosjekter

Oversikt over NRs prosjekter

For å se på et mindre utvalg av prosjekter innenfor en avdeling eller forskningsområde, kryss av på de aktuelle boksene. Hvis flere bokser avmerkes, vil søket gi prosjekter som tilfredsstiller minst en av de avkryssede boksene i hver av søylene med avkryssede bokser.

Sider

Model for uncertainty analysis

The project partner for this project was Gassco, which is the operator of the transport system for natural gas from the Norwegian continental shelf to Europe .
 
Gassco develops an annual Transport Plan to ensure efficient utilisation  and development of the gas infrastructure. NR was involved in this process by developing a model for performing uncertainty analyses for both gas volume rates and gas quality. This model will be used by Gassco to analysis uncertainty related to future gas forecasts.
 

Model selection and model verification for point processes (PointProcess)

Many natural systems such as wildfires, disease occurrences, plant and cellular systems, and animal colonies are observed as point patterns in time, space or space and time. In this project, we will develop new methodology for validating and selecting the most appropriate model for a given data set using Bayesian and decision theoretic principles.

Modeling of resistance to antibiotics

Pills in a boxThe efficiency of antibiotics has over a long period led to overuse and misuse, causing the bacteria to develop resistance to one or more antibacterial agents. Infections and diseases that were successfully treated by antibiotics are now becoming an increasing public health problem. 

Modeling transmission of infectious diseases in aquaculture

Infectious diseases constitute a constant threat to the Norwegian fish farming industry with major economic implications, in addition to being a problem for fish welfare and the environment. Norwegian Computing Center develop stochastic simulation models to describe how infectious diseases are transmitted between fish farms, including models for infectious salmon anaemia, pancras disease and sea lice.

MonCO2 - Monitoring Geological CO2 storage

The full project name is Monitoring Geological CO2 Storage: Quantitative CO2 Prediction with Uncertainty from Physical Modeling and Multiple Time-Lapse Data Types. The project is funded by the Norwegian Research Council and the industrial partners Statoil and ExxonMobil. We collaborate with the University of Bergen and Stanford University to develop improved methods for quantitative prediction of the distributions of CO2 in subsurface storage sites.

MOSKUS – MObile musculoSKeletal User Self-management

The MOSKUS project is about to develop a smart ICT solution to support self-management for patients suffering from arthritis, a prevalent and debilitating chronic disease. Self-management education using ICT tools can empower patients to become effective health-care participants; thus, saving costs in the health care sector and improving the clinical outcome.

MOSKUS – MObile musculoSKeletal User Self-management

MOSKUS prosjektet er i ferd med å utvikle en smart IKT-løsning som støtter egenmestring for pasienter med revmatisk sykdom. Egenmestring basert på IKT-verktøy kan gi pasienter mulighet til å bli aktive deltakere i egen helsesituasjon. Når pasienten selv kan ta ansvar for sykdomsmestring kan utgifter i samfunnet til helse og omsorg reduseres, samtidig som man øker den kliniske effekten.

MOVIS – Performance Monitoring System for Video Streaming Networks

When watching streamed video over the Internet consumers are annoyed by disturbances in service quality. In the delivery chain live video content is streamed by a content provider through the network of an Internet Service Provider (ISP) to the consumer's home network, and then shown on a PC. Should a consumer experience reduced quality a variety of reasons can apply along the entire delivery chain. Monitoring service quality can help to identify the reasons for reduced quality.In an assessment process a test panel have evaluated video content streamed under various conditions.

Sider

Postadresse:
Norsk Regnesentral
Postboks 114 Blindern
0314 Oslo
Besøksadresse:
Norsk Regnesentral
Gaustadalleen 23a
Kristen Nygaards hus
0373 Oslo
Tlf:
(+47) 22 85 25 00
Adresse Hvordan komme til NR
Sosiale media Del på sosiale media
Personvernerklæring Personvernerklæring
Postadresse: Norsk Regnesentral, Postboks 114 Blindern, 0314 Oslo
Besøksadresse: Norsk Regnesentral, Gaustadalleen 23a, Kristen Nygaards hus, 0373 Oslo
Tlf: (+47) 22 85 25 00
AdresseHvordan komme til NR