Browsing Publikasjoner fra CRIStin - SINTEF AS by Title
Now showing items 1086-1105 of 5674
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Datastruktur for dokumentasjon av naturbaserte løsninger – et verktøy
(Klima 2050 Report;19, Research report, 2020)Naturbaserte løsninger (NBL) for håndtering av overvann i urbane strøk finnes i mange former og variasjoner, noe som gjør at det er vanskelig å ha et felles rammeverk som kan integrere alle spesifikke aspekter ved disse ... -
Dating persons with physical disabilities: the perceptions of South Africans without disabilities
(Journal article; Peer reviewed, 2017)There is good reason to believe that the attitudes of persons without disability towards dating a person with a physical disability might be unfavourable. However, in general, and in the Global South in particular, there ... -
Deactivation of Co-Based Fischer−Tropsch Catalyst by Aerosol Deposition of Potassium Salts
(Journal article; Peer reviewed, 2018)A 20%Co/0.5%Re/γAl2O3 Fischer−Tropsch catalyst was poisoned by four potassium salts (KNO3, K2SO4, KCl, and K2CO3) using the aerosol deposition technique, depositing up to 3500 ppm K as solid particles. Standard characterization ... -
A Decade of Research on Autonomous Agile Teams: A Summary of the Third International Workshop
(Peer reviewed; Journal article, 2020)Ever since the agile manifesto was created in 2001, the research community has devoted attention to autonomous teams. This article first examines publications on autonomous agile teams to illustrate how the research has ... -
A decade of research on patterns and architectures for IoT security
(Peer reviewed; Journal article, 2022)Security of the Internet of Things (IoT)-based Smart Systems involving sensors, actuators and distributed control loop is of paramount importance but very difficult to address. Security patterns consist of domain-independent ... -
Decision Process in One-of-a-kind Production
(Journal article; Peer reviewed, 2017) -
A Decision Support System for preclinical assessment of nanomaterials in medical products: the REFINE DSS
(Peer reviewed; Journal article, 2022)The application of nanomaterials in medicine has led to novel pharmaceuticals and medical devices that have demonstrated a strong potential for increasing the efficacy/performance and safety of therapeutic and diagnostic ... -
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 ... -
Deconstructing (e)health literacy: aspects that promote and inhibit understanding of health information in breast cancer patient pathways
(Peer reviewed; Journal article, 2022)Purpose: Deconstructing current definitions of “health literacy (HL)” and “eHealth literacy (eHL)”, into the core notion of “understanding health information (HI)”, this study provides insights into what promotes and ... -
DECRIS - Risk and Decision Systems for Critical Infrastructures. Metode og verktøy for en samlet risikovurdering av kritiske infrastrukturer
(SINTEF Rapport;, Research report, 2009)Prosjektet DECRIS er finansiert av Norges forskningsråd under SAMRISK-programmet. Det er et samarbeidsprosjekt mellom SINTEF, FFI og NTNU. Prosjektet har utviklet og tilpasset metoder for risikovurdering for kritisk ... -
Deep CNN-LSTM With Self-Attention Model for Human Activity Recognition Using Wearable Sensor
(Peer reviewed; Journal article, 2022)Human Activity Recognition (HAR) systems are devised for continuously observing human behavior - primarily in the fields of environmental compatibility, sports injury detection, senior care, rehabilitation, entertainment, ... -
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 customization of multi-tenant SaaS using intrusive microservices
(Journal article; Peer reviewed, 2018)Enterprise software needs to be customizable, and the customization needs from a customer are often beyond what the software vendor can predict in advance. In the on-premises era, customers do deep customizations beyond ... -
Deep learning based decomposition for visual navigation in industrial platforms
(Peer reviewed; Journal article, 2021)In the heavy asset industry, such as oil & gas, offshore personnel need to locate various equipment on the installation on a daily basis for inspection and maintenance purposes. However, locating equipment in such GPS ... -
Deep learning based hashtag recommendation system for multimedia data
(Peer reviewed; Journal article, 2022)This work aims to provide a novel hybrid architecture to suggest appropriate hashtags to a collection of orpheline tweets. The methodology starts with defining the collection of batches used in the convolutional neural ... -
Deep learning for image-based liver analysis — A comprehensive review focusing on malignant lesions
(Peer reviewed; Journal article, 2022)Deep learning-based methods, in particular, convolutional neural networks and fully convolutional networks are now widely used in the medical image analysis domain. The scope of this review focuses on the analysis using ... -
Deep Learning for Improved Precision and Reproducibility of Left Ventricular Strain in Echocardiography: A Test-Retest Study
(Peer reviewed; Journal article, 2023)Aims: Assessment of left ventricular (LV) function by echocardiography is hampered by modest test-retest reproducibility. A novel artificial intelligence (AI) method based on deep learning provides fully automated measurements ... -
Deep learning for pedestrian collective behavior analysis in smart cities: A model of group trajectory outlier detection
(Peer reviewed; Journal article, 2021)This paper introduces a new model to identify collective abnormal human behaviors from large pedestrian data in smart cities. To accurately solve the problem, several algorithms have been proposed in this paper. These can ... -
Deep learning for prediction of depressive symptoms in a large textual dataset
(Peer reviewed; Journal article, 2021)Depression is a common illness worldwide with potentially severe implications. Early identification of depressive symptoms is a crucial first step towards assessment, intervention, and relapse prevention. With an increase ...