Doctoral presentations of current interest, where the thesis is available in Munin:

07 May 2021: Miguel Ángel Tejedor Hernández

Glucose Regulation for In-Silico Type 1 Diabetes Patients Using Reinforcement Learning

11 May 2021: David Andreas Thomas Werner

Development of a prognostic model for unfavorable outcome after lumbar microdiscectomy

11 May 2021: Rolf-Ole Rydeng Jenssen

Radar System Development for Drone Borne Applications with Focus on Snowpack Parameters

14 May 2021: Priya Bhide

The role of ovarian reserve markers in fertility and fertility treatment

20 May 2021: Inger Lund-Kordahl

Studies on the Chain of Survival in Out-of-Hospital Cardiac Arrest

20 May 2021: Lars Dalheim

Porosira glacialis as a possible source of lipids for human consumption and aquaculture feed

21 May 2021: Gregor Decristoforo

Numerical simulations and stochastic modeling of intermittent fluctuations in magnetized plasmas

21 May 2021: Juncal Garcia Garcia

Exploring the roles of TRIM27 and TRIM32 in autophagy

21 May 2021: Veronika Gjertsen Rypdal

Prediction of unfavorable outcome in Juvenile Idiopathic Arthritis (JIA) and assessment of the long-term outcomes in JIA-associated uveitis – A prospective Nordic multicenter study of JIA from childhood to adulthood

25 May 2021: Franziska Jensen

Kontrastive Feldermodelle als didaktische Werkzeuge im universitären DaF-Unterricht für norwegische Muttersprachler

28 May 2021: Ole Andreas Nilsen

The influence of lifestyle on peak bone mass in Norwegian boys and girls between 15-19 years of age. The Tromsø study, Fit Futures

28 May 2021: Ashenafi Zebene Woldaregay

EDMON - Electronic Disease Surveillance and Monitoring Network: A Personalized Health Model-based Digital Infectious Disease Detection Mechanism using Self-Recorded Data from People with Type 1 Diabetes

  • Trophic and fitness correlates of mercury and organochlorine compound residues in egg-laying Antarctic petrels 

    Carravieri, Alice; Warner, Nicholas Alexander; Herzke, Dorte; Brault-Favrou, Maud; Tarroux, Arnaud; Fort, Jérôme; Bustamante, Paco; Descamps, Sebastien (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-24)
    Understanding the drivers and effects of exposure to contaminants such as mercury (Hg) and organochlorine compounds (OCs) in Antarctic wildlife is still limited. Yet, Hg and OCs have known physiological and fitness effects in animals, with consequences on their populations. Here we measured total Hg (a proxy of methyl-Hg) in blood cells and feathers, and 12 OCs (seven polychlorinated biphenyls, PCBs, ...
  • Unternehmen Mittelklasse, ein unpassender Kastrat und wer am lautesten schreit: Das schwierige Verhältnis der Times zu Giovanni Battista Velluti 

    Losleben, Katrin (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-15)
    Nach dem Erfolg, den Giovanni Battista Velluti (1780–1861) als Armando im Giacomo Meyerbeers <i>Crociato in Egitto</i> 1824 zunächst im La Fenice in Venedig, kurz darauf, im Mai, im Teatro della Pergola in Florenz gefeiert hatte, debütierte der letzte berühmte Opernkastrat am 30. Juni 1825 im King’s Theatre der englischen Hauptstadt. Zu diesem Zeitpunkt war er wenigstens den Leser*innen der jüngst ...
  • Can We Automate Diagrammatic Reasoning? 

    Sekh, Arif Ahmed; Dogra, Debi Prasad; Kar, Samarjit; Roy, Partha Pratim; Prosad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-05-06)
    Diagrammatic reasoning (DR) problems are well known. However, solving DR problems represented in 4 × 1 Raven’s Progressive Matrix (RPM) form using computer vision and pattern recognition has not yet been tried. Emergence of deep learning techniques aided by advanced computing can be exploited to solve such DR problems. In this paper, we propose a new learning framework by combining LSTM and Convolutional ...
  • Video trajectory analysis using unsupervised clustering and multi-criteria ranking 

    Sekh, Arif Ahmed; Dogra, Debi Prasad; Kar, Samarjit; Roy, Partha Pratim (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-05-13)
    Surveillance camera usage has increased significantly for visual surveillance. Manual analysis of large video data recorded by cameras may not be feasible on a larger scale. In various applications, deep learning-guided supervised systems are used to track and identify unusual patterns. However, such systems depend on learning which may not be possible. Unsupervised methods relay on suitable features ...
  • Multi-frequency SuperDARN radar observations of the modulated ionosphere by high-power radio-waves at EISCAT 

    Mahmoudian, A.; Yeoman, T. K.; Senior, A.; Kosch, M.; Scales, W. A.; Shi, X.; Ruohoniemi, M.; Rietveld, Michael T (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-04-02)
    This paper presents the first joint observations of multi-frequency SuperDARN (Super Dual Auroral Radar Network) radar of the heated ionosphere by high-power high-frequency (HF) ground-based radio-waves along with the stimulated electromagnetic emissions (SEE) measurements. The unique heating experiment design at EISCAT (The European Incoherent Scatter Scientific Association) including fine frequency ...

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