Browsing Publikasjoner fra CRIStin - NTNU by Title
Now showing items 21071-21090 of 38672
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m - f - neuter: kjønnsparadokser på nett
(Chapter; Peer reviewed, 2002) -
M-ficolin: a valuable biomarker to identify leukaemia from juvenile idiopathic arthritis
(Peer reviewed; Journal article, 2021)Objective: Distinction on clinical grounds between acute lymphoblastic leukaemia presenting with arthropathy (ALLarthropathy) and juvenile idiopathic arthritis (JIA) is difficult, as the clinical and paraclinical signs of ... -
M.H. Bjørk og medarbeidere svarer
(Peer reviewed; Journal article, 2020) -
Machine Learning (ML) diffusion in the design process: A study of Norwegian design consultancies
(Peer reviewed; Journal article, 2023) -
Machine Learning (ML)-Based Prediction and Compensation of Springback for Tube Bending
(Chapter, 2021)Bent tubes are extensively used in the manufacturing industry to meet demands for lightweight and high performance. As one of the most significant behaviors affecting the dimensional accuracy in tube bending, springback ... -
Machine Learning Aided Static Malware Analysis: A Survey and Tutorial
(Chapter, 2018)Malware analysis and detection techniques have been evolving during the last decade as a reflection to development of different malware techniques to evade network-based and host-based security protections. The fast growth ... -
Machine learning algorithm for prediction of stuck pipe incidents using statistical data: case study in middle east oil fields
(Peer reviewed; Journal article, 2022)One of the most troublesome issues in the drilling industry is stuck drill pipes. Drilling activities will be costly and time-consuming due to stuck pipe issues. As a result, predicting a stuck pipe can be more useful. ... -
Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury
(Peer reviewed; Journal article, 2020)Objective We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting We performed logistic regression ... -
A Machine Learning and Blockchain Based Efficient Fraud Detection Mechanism
(Peer reviewed; Journal article, 2022)In this paper, we address the problems of fraud and anomalies in the Bitcoin network. These are common problems in e-banking and online transactions. However, as the financial sector evolves, so do the methods for fraud ... -
Machine learning and CFD for mapping and optimization of CO2 ejectors
(Peer reviewed; Journal article, 2021)In this study, a novel simulation-based algorithm for CO2 ejector design and performance evaluation is presented. The algorithm is based on an automated Computational Fluid Dynamics (CFD) workflow that can account for ... -
A Machine Learning Approach to Analyze Natural Hazards Accidents Scenarios
(Peer reviewed; Journal article, 2022)Climate change has contributed to an increasing frequency and severity of natural hazards accidents over recent years, and the increasing trend is expected to continue and escalate. Globally, demographics are changing and ... -
A Machine Learning Approach to Investigate Fronto-Parietal Neural Ensemble Dynamics During Complex
(Chapter, 2020)Brain circuits exhibit very complex dynamics, where individual neurons fire action potentials determining coordinated activity patterns. During behavior, a multitude of brain areas are engaged in planning and execution. A ... -
A machine learning approach to predict chattering alarms
(Peer reviewed; Journal article, 2020)The alarm system plays a vital role to ensure safety and reliability in the process industry. Ideally, an alarm should inform the operator about critical conditions only and provide guidance to a set of corrective actions ... -
A Machine Learning Approach to Predict Post-stroke Fatigue. The Nor-COAST study
(Journal article; Peer reviewed, 2014)Objective: This study aimed to predict fatigue 18 months post-stroke by utilizing comprehensive data from the acute and sub-acute phases after stroke in a machine-learning set-up. Design: A prospective multicenter ... -
A Machine Learning Approach to Predict the Materials' Susceptibility to Hydrogen Embrittlement
(Journal article; Peer reviewed, 2023) -
Machine Learning Approaches to Automatically Detect Glacier Snow Lines on Multi-Spectral Satellite Images
(Peer reviewed; Journal article, 2022)Documenting the inter-annual variability and the long-term trend of the glacier snow line altitude is highly relevant to document the evolution of glacier mass changes. Automatically identifying the snow line on glaciers ... -
Machine learning augmented reduced-order models for FFR-prediction
(Peer reviewed; Journal article, 2021)Computational predictions in cardiovascular medicine have largely relied on explicit models derived from physical and physiological principles. Recently, the application of artificial intelligence in cardiovascular medicine ... -
Machine Learning Based Heuristic Technique for Multi-response Machining Process
(Peer reviewed; Journal article, 2020)Manufacturing process variables influence the quality of products substantially. It is unquestionably difficult to model the manufacturing processes that include a large number of variables and responses. Development of ... -
Machine Learning Based Prediction of Nanoscale Ice Adhesion on Rough Surfaces
(Peer reviewed; Journal article, 2021)It is widely recognized that surface roughness plays an important role in ice adhesion strength, although the correlation between the two is far from understood. In this paper, two approaches, molecular dynamics (MD) ...