Browsing Publikasjoner fra CRIStin by Document Types "Chapter"
Now showing items 241-260 of 1079
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Data Assimilation for Ocean Drift Trajectories Using Massive Ensembles and GPUs
(Chapter, 2020)In this work, we perform fully nonlinear data assimilation of ocean drift trajectories using multiple GPUs. We use an ensemble of up to 10000 members and the sequential importance resampling algorithm to assimilate ... -
Data Assimilation for Ocean Drift Trajectories Using Massive Ensembles and GPUs
(Chapter, 2020)In this work, we perform fully nonlinear data assimilation of ocean drift trajectories using multiple GPUs. We use an ensemble of up to 10000 members and the sequential importance resampling algorithm to assimilate ... -
Data quality issues for vibration sensors: a case study in ferrosilicon production
(Chapter, 2022)Digitisation in the mining and metal processing industries plays a key role in their modernisation. Production processes are more and more supported by a variety of sensors that produce large amounts of data that meant to ... -
Data quality issues in solar panels installations: a case study
(Chapter, 2022)Solar photovoltaics (PV) is becoming an important source of global electricity generation. Modern PV installations come with a variety of sensors attached to them for monitoring purposes (e.g., maintenance, prediction of ... -
Data Safety, Sources, and Data Flow in the Offshore Industry
(Chapter; Peer reviewed, 2021)Digitization may provide increased access to and more efficient use of real-time and historical data, internally as well as externally in an organization. However, when information from industrial control systems (ICS) ... -
Data-driven Household Load Flexibility Modelling: Shiftable Atomic Load
(Chapter; Peer reviewed, 2018)To keep a stable power system, there should always be balance between the generation and consumption of electricity. In this study, a flexibility modelling method for atomic loads which is based on high resolution appliance ... -
Data-driven sea state estimation for vessels using multi-domain features from motion responses
(Chapter; Peer reviewed, 2021)Situation awareness is of great importance for autonomous ships. One key aspect is to estimate the sea state in a real-time manner. Considering the ship as a large wave buoy, the sea state can be estimated from motion ... -
DataCloud: Enabling the Big Data Pipelines on the Computing Continuum
(Chapter, 2021) -
Datasets for grey-box model identification from representative archetypes of apartment blocks in Norway
(SINTEF Proceedings;5, Chapter; Peer reviewed; Conference object, 2020)Grey-box models combine a relatively simple physical description of the building with a data-driven inference of key parameters and are often used for this purpose. A challenge with grey-box models is that the model ... -
Deconfliction and Surface Generation from Bathymetry Data Using LR B-splines
(Chapter, 2017)A set of bathymetry point clouds acquired by different measurement techniques at different times, having different accuracy and varying patterns of points, are approximated by an LR B-spline surface. The aim is to represent ... -
Decoupled Active and Reactive Power Controllers for Damping Low-Frequency Oscillations using Virtual Synchronous Machines
(Chapter; Peer reviewed, 2023)In this paper, a power oscillation damping (POD) controller embedded in virtual synchronous machines (VSMs) is proposed. This controller suggests the decoupled use of both active and reactive powers to damp low-frequency ... -
Deep Complex Convolutional Recurrent Network for Multi-Channel Speech Enhancement and Dereverberation
(Chapter, 2021)This paper proposes a neural network based system for multi-channel speech enhancement and dereverberation. Speech recorded indoors by a far field microphone, is invariably degraded by noise and reflections. Recent single ... -
Deep Reinforcement Learning Attitude Control of Fixed Wing UAVs Using Proximal Policy Optimization
(Chapter; Peer reviewed, 2019)Contemporary autopilot systems for unmanned aerial vehicles (UAVs) are far more limited in their flight envelope as compared to experienced human pilots, thereby restricting the conditions UAVs can operate in and the types ... -
Deep Reinforcement Learning for Long Term Hydropower Production Scheduling
(Chapter; Peer reviewed, 2020)We explore the use of deep reinforcement learning to provide strategies for long term scheduling of hydropower production. We consider a use-case where the aim is to optimise the yearly revenue given week-by-week inflows ... -
Defining a Remote Work Policy: Aligning Actions and Intentions
(Chapter, 2023)After the long period of forced work from home, many knowledge workers have not only developed a strong habit of remote work, but also consider flexibility as their personal right and no longer as a privilege. Existing ... -
Defining Ship Autonomy by Characteristic Factors
(SINTEF Proceedings;3, Chapter, 2019)Several papers have proposed ways to define levels of autonomy (LOA), i.e. how responsibility is shared between an automation system and a human when the automation system to some degree can operate independently of the ... -
Deliverance from Trust through a Redundant Array of Independent Net-storages in Cloud Computing
(Chapter, 2011)Cloud storage services are gaining more and more attention. Surveys suggest that the confidentiality issue is one of the major obstacles for users to use cloud storage services to keep sensitive data. This paper proposes ... -
Demand response with shiftable volume in an equilibrium model of the power system
(Chapter; Peer reviewed, 2017) -
Demand-controlled ventilation in schools: Influence of base ventilation rates on subjective symptoms, perceived indoor environment and young adults' learning performance
(SINTEF Proceedings;9, Chapter; Peer reviewed; Conference object, 2021)The ventilation airflow rates in a demand-controlled ventilation strategy typically vary between a base (Vmin) and a maximum ventilation rate (Vmax). Classrooms have relatively short but intense hours of occupancy and a ...