6 research outputs found
AMADEA - Adaptable Maritime Decision Support Architecture
Here, we present a reference model for maritime decision support systems. We establish a common terminology for the components and structure of such systems, describe a number of general-purpose components that can be developed once and then reused in many different contexts, and give practical advice for implementers. We also provide concrete examples of decision support systems for a variety of maritime systems and operations, including offshore lifting operations, fisheries, and marine seismics.AMADEA - Adaptable Maritime Decision Support ArchitectureacceptedVersio
lmproVEDO åpen rapport - Åpne resultater fra KMB-prosjektet lmproVEDO
Prosjektet lmproVEDO har hatt som hovedmål å utvikle metoder og verktøy for å redusere energibruken i den norske skipsflåten. Prosjektet har utviklet metoder og verktøy som fokuserer på både drift og design.
Resultatene fra prosjektet er tatt i bruk i flere andre prosjekt og har hatt industriell verdi.
Denne rapporten beskriver kort hva som er gjort i prosjektet. Hovedfokus i prosjektet har vært utvikling av KPl'er for fiskefartøy, programvare for logging, aggregering og analyse av operasjonelle data (STIM, Ratatosk) og programvare for beslutningsstøtte for design av fartøy (MachOS). Dette er kort beskrevet i rapporten, for mer utførlig beskrivelse av programvare henvises det til den enkelte programvarens dokumentasjon og til KPl-definisjonene i separat regneark.
En sentral del av prosjektet har vært å benytte verktøy utviklet i prosjektet til innhenting og analyse av operasjonelle data fra tråleren M/S Prestfjord. Dataene og analysen av disse dataene er presentert i SINTEF rapport F27593 "lmproVEDO detaljert rapport".Norges Forskningsråd, Rolls-Royce Marine, Fiskeri- og havbruksnæringens ForskningsfondpublishedVersio
SMARTFISH H2020 D5.3: FishData analysis (Open access revision)
The goal of SMARTFISH H2020 is to develop, test and promote a suite of high-tech systems for the EU fishing sector, thereby optimizing resource efficiency, improving automatic data collection for fish stock assessment, provide evidence of compliance with fishery regulations and reduce the ecological impact of the industry. Here, we present a prototype system for visualising and studying information about catch composition and catch efficiency in fisheries. The system mainly consists of two web applications. One is based on data from automatic catch recording technologies and other onboard sensors, and shows information about a limited number of vessels. The other is based on publicly available official catch reports from the entire fishing fleet. SMARTFISH H2020 has also contributed to the development of a third application which provides forecasts of marine environmental conditions. The applications are aimed at three stakeholder groups: fishers, who may use them as decision support when planning their operations; fisheries managers, who may use them for real-time monitoring and control; and marine researchers, who may use them in a stock assessment setting. This is an open-access revision of a confidential deliverable. Some of the text in the original report has been removed.SMARTFISH H2020 D5.3: FishData analysis (Open access revision)publishedVersio
SMARTFISH H2020 D5.3: FishData analysis (Open access revision)
The goal of SMARTFISH H2020 is to develop, test and promote a suite of high-tech systems for the EU fishing sector, thereby optimizing resource efficiency, improving automatic data collection for fish stock assessment, provide evidence of compliance with fishery regulations and reduce the ecological impact of the industry. Here, we present a prototype system for visualising and studying information about catch composition and catch efficiency in fisheries. The system mainly consists of two web applications. One is based on data from automatic catch recording technologies and other onboard sensors, and shows information about a limited number of vessels. The other is based on publicly available official catch reports from the entire fishing fleet. SMARTFISH H2020 has also contributed to the development of a third application which provides forecasts of marine environmental conditions. The applications are aimed at three stakeholder groups: fishers, who may use them as decision support when planning their operations; fisheries managers, who may use them for real-time monitoring and control; and marine researchers, who may use them in a stock assessment setting. This is an open-access revision of a confidential deliverable. Some of the text in the original report has been removed
Effect of task-correlated physiological fluctuations and motion in 2D and 3D echo-planar imaging in a higher cognitive level fMRI paradigm
Purpose: To compare 2D and 3D echo-planar imaging (EPI) in a higher cognitive level fMRI paradigm. In particular, to study the link between the presence of task-correlated physiological fluctuations and motion and the fMRI contrast estimates from either 2D EPI or 3D EPI datasets, with and without adding nuisance regressors to the model. A signal model in the presence of partly task-correlated fluctuations is derived, and predictions for contrast estimates with and without nuisance regressors are made.
Materials and Methods: Thirty-one healthy volunteers were scanned using 2D EPI and 3D EPI during a virtual environmental learning paradigm. In a subgroup of 7 subjects, heart rate and respiration were logged, and the correlation with the paradigm was evaluated. FMRI analysis was performed using models with and without nuisance regressors. Differences in the mean contrast estimates were investigated by analysis-of-variance using Subject, Sequence, Day, and Run as factors. The distributions of group level contrast estimates were compared.
Results: Partially task-correlated fluctuations in respiration, heart rate and motion were observed. Statistically significant differences were found in the mean contrast estimates between the 2D EPI and 3D EPI when using a model without nuisance regressors. The inclusion of nuisance regressors for cardiorespiratory effects and motion reduced the difference to a statistically non-significant level. Furthermore, the contrast estimate values shifted more when including nuisance regressors for 3D EPI compared to 2D EPI.
Conclusion: The results are consistent with 3D EPI having a higher sensitivity to fluctuations compared to 2D EPI. In the presence partially task-correlated physiological fluctuations or motion, proper correction is necessary to get expectation correct contrast estimates when using 3D EPI. As such task-correlated physiological fluctuations or motion is difficult to avoid in paradigms exploring higher cognitive functions, 2D EPI seems to be the preferred choice for higher cognitive level fMRI paradigms
Development and assessment of novel technologies improving the fishing operation and on board processing with respect to environmental impact and fish quality (DANTEQ)
Bærekraftig høsting av villfanget fisk er en av de viktigste utfordringene i det globale bildet når det gjelder å skaffe tilstrekkelige mengder fisk. Det ligger et stort potensial i å høste fisk på en bedre måte. Norge er langt fremme både når det gjelder teknologisk utstyrsutvikling og anvendelse av nye fangstkonsepter, men det er fortsatt betydelige utfordringer spesielt i grensesnittet mellom den nye teknologien og fangstbehandling. Konvensjonelt fiskeri gjennomføres med flere forskjellige fartøykonsepter og redskapstyper. Felles for alle er at råstoffkvalitet og fangstinntekt henger sammen med fangst- og produksjonsprosess ombord med tilhørende investerings- og driftskostnader. Fiskefartøy har i langt større grad enn andre produksjonslokaliteter begrenset handlingsrom for å optimalisere prosessen med hensyn til økonomi og andre parametere som f.eks. miljøbelastning. Dette kommer i første rekke fra begrenset tilgjengelig volum og relativt kostbare tilgjengelige energikilder som f.eks. konvensjonelle oljedrevne motordrifter som benyttes til produksjon av elektrisk energi. Gjennom prosjektet DANTEQ har det blitt bygget ny kompetanse og utviklet metoder for å optimalisere håndtering av fisk ombord med hensyn til råstoffkvalitet og energieffektivitet. Arbeidet i DATNEQ har vært delt opp i fire ulike arbeidsområder (RA). Innen RA1 ble effekten av korttids levendelagring av fisk før slakting og elektrobedøving studert. I RA2 var fokuset kjøle- og frysesystemer ombord og effekt på råstoffkvalitet. I RA3 var fokuset å logge energiforbruk fra ulike kilder ombord på trålere for videre å kunne benytte disse dataene til energieffektiv drift av fiskefartøy. I RA4 ble det utviklet matematiske modeller og metoder for simulering av fangstbehandling og fabrikkprosesser ombor