Browsing Publikasjoner fra CRIStin - NTNU by Title

Now showing items 11509-11528 of 37349

    • Enhancing the mechanical durability of icephobic surfaces by introducing autonomous self-healing function 

      Zhuo, Yizhi; Håkonsen, Verner; He, Zhiwei; Xiao, Senbo; He, Jianying; Zhang, Zhiliang (Journal article; Peer reviewed, 2018)
      Ice accretion presents a severe risk for human safety. Despite great efforts for developing icephobic surfaces (the surface with an ice adhesion strength below 100 kPa) have been devoted, expanding the lifetime of ...

    • Enhancing the vocabulary learning skills of autistic children using augmented reality: a participatory design perspective 

      El Shemi, Ibrahim; Urrea, Ana Lucia; Erena-Guardia, Gema; Saldaña, David; Vulchanova, Mila Dimitrova; Giannakos, Michail (Chapter, 2023)
      Many autistic children1 face challenges with vocabulary learning. Augmented Reality (AR) has the potential to improve their learning process by leveraging their visuo-perceptual strengths. However, there is a gap in the ...

    • Enhancing Usage Control for Performance: An Architecture for Systems of Systems 

      Gkioulos, Vasileios; Rizos, Athanasios; Michailidou, Christina; Mori, Paolo; Saracino, Andrea (Journal article; Peer reviewed, 2019)
      The distributiveness and heterogeneity of today’s systems of systems, such as the Internet of Things (IoT), on-line banking systems, and contemporary emergency information systems, require the integration of access and ...

    • ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries 

      Thompson, Paul M.; Jahanshad, Neda; Ching, Christopher R.K.; Salminen, Lauren E.; Thomopoulos, Sophia I.; Bright, Joanna; Baune, Bernhard T.; Bertolin, Sara; Bralten, Janita; Bruin, Willem B.; Bulow, Robin; Chen, Jian; Chye, Yann; Dannlowski, Udo; de Kovel, Carolien G.F.; Donohoe, Gary; Eyler, Lisa T.; Faraone, Stephen V.; Favre, Pauline; Filippi, Courtney A.; Frodl, Thomas; Garijo, Daniel; Gil, Yolanda; Grabe, Hans J.; Grasby, Katrina L.; Hajek, Tomas; Han, Laura K.M.; Hatton, Sean N.; Hilbert, Kevin; Ho, Tiffany C.; Holleran, Laurena; Homuth, Georg; Hosten, Norbert; Houenou, Josselin; Ivanov, Iliyan; Jia, Tianye; Kelly, Sinead; Klein, Marieke; Kwon, Jun Soo; Laansma, Max A.; Leerssen, Jeanne; Lueken, Ulrike; Nunes, Abraham; O'Neill, Joseph; Opel, Nils; Piras, Fabrizio; Piras, Federica; Postema, Merel C.; Pozzi, Elena; Shatokhina, Natalia; Soriano-Mas, Carles; Spalletta, Gianfranco; Sun, Daqiang; Teumer, Alexander; Tilot, Amanda K.; Tozzi, Leonardo; van der Merwe, Celia; van Someren, Eus J.W.; van Wingen, Guido A.; Völzke, Henry; Walton, Esther; Wang, Lei; Winkler, Anderson M.; Wittfeld, Katharina; Wright, Margaret J.; Yun, Je-Yeon; Zhang, Guohao; Zhang-James, Yanli; Adhikari, Bhim M.; Agartz, Ingrid; Aghajani, Moji; Aleman, André; Althoff, Robert R.; Altmann, Andre; Andreassen, Ole Andreas; Baron, David A.; Bartnik-Olson, Brenda L.; Bas-Hoogendam, Janna Marie; Baskin-Sommers, Arielle R.; Bearden, Carrie E.; Berner, Laura A.; Boedhoe, Premika S.W.; Brouwer, Rachel M.; Buitelaar, Jan K.; Caeyenberghs, Karen; Cecil, Charlotte A.M.; Cohen, Ronald A.; Cole, James H.; Conrod, Patricia J.; De Brito, Stephane A.; de Zwarte, Sonja M.C.; Dennis, Emily L.; Desrivieres, Sylvane; Dima, Danai; Ehrlich, Stefan; Esopenko, Carrie; Fairchild, Graeme; Fisher, Simon E.; Fouche, Jean-Paul; Francks, Clyde; Frangou, Sophia; Franke, Barbara; Garavan, Hugh P.; Glahn, David C.; Groenewold, Nynke A.; Gurholt, Tiril Pedersen; Gutman, Boris A.; Hahn, Tim; Harding, Ian H.; Hernaus, Dennis; Hibar, Derrek P.; Hillary, Frank G.; Hoogman, Martine; Hulshoff Pol, Hilleke E.; Jalbrzikowski, Maria; Karkashadze, George A.; Klapwijk, Eduard T.; Knickmeyer, Rebecca C.; Kochunov, Peter; Koerte, Inga K.; Kong, Xiang-Zhen; Liew, Sook-Lei; Lin, Alexander P.; Logue, Mark W.; Luders, Eileen; Macciardi, Fabio; Mackey, Scott; Mayer, Andrew R.; McDonald, Carrie R.; McMahon, Agnes B.; Medland, Sarah E.; Modinos, Gemma; Morey, Rajendra A.; Mueller, Sven C.; Mukherjee, Pratik; Namazova-Baranova, Leyla; Nir, Talia M; Olsen, Alexander; Paschou, Peristera; Pine, Daniel S.; Pizzagalli, Fabrizio; Rentería, Miguel E.; Rohrer, Jonathan D.; Sämann, Philipp G.; Schmaal, Lianne; Schumann, Gunter; Shiroishi, Mark S.; Sisodiya, Sanjay M.; Smit, Dirk J.A.; Sønderby, Ida Elken; Stein, Dan J.; Stein, Jason L.; Tahmasian, Masoud; Tate, David F.; Turner, Jessica A.; van den Heuvel, Odile A; Van Der Wee, Nic J.A.; van der Werf, Ysbrand D.; van Erp, Theo G.M.; van Haren, Neeltje E.M.; van Rooij, Daan; van Velzen, Laura S.; Veer, Ilya M.; Veltman, Dick J.; Villalon-Reina, Julio E.; Walter, Henrik; Whelan, Christopher D.; Wilde, Elisabeth A.; Zarei, Mojtaba; Zelman, Vladimir (Peer reviewed; Journal article, 2020)
      This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in ...

    • ENIGMA brain injury: Framework, challenges, and opportunities 

      Dennis, Emily L.; Baron, David; Bartnik-Olson, Brenda L.; Caeyenberghs, Karen; Esopenko, Carrie; Hillary, Frank G.; Kenney, Kimbra; Koerte, Inga K.; Lin, Alexander P.; Mayer, Andrew R.; Mondello, Stefania; Olsen, Alexander; Thompson, Paul M.; Tate, David; Wilde, Elisabeth A. (Peer reviewed; Journal article, 2020)
      Traumatic brain injury (TBI) is a major cause of disability worldwide, but the heterogeneous nature of TBI with respect to injury severity and health comorbidities make patient outcome difficult to predict. Injury severity ...

    • ENIGMA-Sleep: Challenges, opportunities, and the road map 

      Tahmasian, Masoud; Aleman, André; Andreassen, Ole; Arab, Zahra; Baillet, Marion; Benedetti, Francesco; Bresser, Tom; Bright, Joanna; Chee, Michael W.L.; Chylinski, Daphne; Cheng, Wei; Deantoni, Michele; Dresler, Martin; Eickhoff, Simon B.; Eickhoff, Claudia R.; Elvsåshagen, Torbjørn; Feng, Jianfeng; Foster-Dingley, Jessica C.; Ganjgahi, Habib; Grabe, Hans J.; Groenewold, Nynke A.; Ho, Tiffany C.; Bong Hong, Seung; Houenou, Josselin; Irungu, Benson; Jahanshad, Neda; Khazaie, Habibolah; Kim, Hosung; Koshmanova, Ekaterina; Kocevska, Desi; Kochunov, Peter; Lakbila-Kamal, Oti; Leerssen, Jeanne; Li, Meng; Luik, Annemarie I.; Muto, Vincenzo; Narbutas, Justinas; Nilsonne, Gustav; O’Callaghan, Victoria S.; Olsen, Alexander; Osorio, Ricardo S.; Poletti, Sara; Poudel, Govinda; Reesen, Joyce E.; Reneman, Liesbeth; Reyt, Mathilde; Riemann, Dieter; Rosenzweig, Ivana; Rostampour, Masoumeh; Saberi, Amin; Schiel, Julian; Schmidt, Christina; Schrantee, Anouk; Sciberras, Emma; Silk, Tim J.; Sim, Kang; Smevik, Hanne; Soares, Jair C.; Spiegelhalder, Kai; Stein, Dan J.; Talwar, Puneet; Tamm, Sandra; Teresi, Giana l.; Valk, Sofie L.; Van Someren, Eus; Vandewalle, Gilles; Van Egroo, Maxime; Völzke, Henry; Walter, Martin; Wassing, Rick; Weber, Frederik D.; Weihs, Antoine; Westlye, Lars Tjelta; Wright, Margaret J.; Wu, Mon-Ju; Zak, Nathalia; Zarei, Mojtaba (Peer reviewed; Journal article, 2021)
      Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, ...

    • Enjoyment as a learning resource: Stories told by students with harmful concentration problems. 

      Løhre, Audhild; Vedul-Kjelsås, Vigdis; Østerlie, Ove (Peer reviewed; Journal article, 2021)
      Having concentration problems is typical within several diagnoses, such as ADHD, dyscalculia and dyslexia. This study aimed to explore how students experience their concentration problems in relation to schoolwork and what ...

    • The enlightening role of explainable artificial intelligence in chronic wound classification 

      Sarp, Salih; Kuzlu, Murat; Wilson, Emmanuel; Cali, Umit; Guler, Ozgur (Peer reviewed; Journal article, 2021)
      Artificial Intelligence (AI) has been among the most emerging research and industrial application fields, especially in the healthcare domain, but operated as a black-box model with a limited understanding of its inner ...

    • The enlightening role of explainable artificial intelligence in medical & healthcare domains: A systematic literature review 

      Ali, Subhan; Akhlaq, Filza; Imran, Ali Shariq; Kastrati, Zenun; Daudpota, Sher Muhammad; Moosa, Muhammad (Peer reviewed; Journal article, 2023)
      In domains such as medical and healthcare, the interpretability and explainability of machine learning and artificial intelligence systems are crucial for building trust in their results. Errors caused by these systems, ...

    • Enriching captivity conditions with natural elements does not prevent the loss of wild-like gut microbiota but shapes its compositional variation in two small mammals 

      Koziol, Adam; Odriozola, Iñaki; Nyholm, Lasse; Leonard, Aoife; San José, Carlos; Pauperio, Joana; Ferreira, Clara; Hansen, Anders J.; Aizpurua, Ostaizka; Gilbert, Marcus Thomas Pius; Alberdi, Antton (Journal article; Peer reviewed, 2022)

    • Enrichment and Representability for Triangulated Categories 

      Steen, Johan; Stevenson, Greg (Journal article; Peer reviewed, 2017)
      Given a fixed tensor triangulated category S we consider triangulated categories T together with an S-enrichment which is compatible with the triangulated structure of T. It is shown that, in this setting, an enriched ...

    • Ensemble and Self-supervised Learning for Improved Classification of Seismic Signals from the Åknes Rockslope 

      Lee, Daesoo; Aune, Erlend; Langet, Nadege; Eidsvik, Jo (Journal article; Peer reviewed, 2022)
      A case study with seismic geophone data from the unstable Åknes rock slope in Norway is considered. This rock slope is monitored because there is a risk of severe flooding if the massive-size rock falls into the fjord. The ...

    • Ensemble distribution for immiscible two-phase flow in porous media 

      Savani, Isha; Bedeaux, Dick; Kjelstrup, Signe; Vassvik, Morten; Sinha, Santanu; Hansen, Alex (Journal article, 2017)
      We construct an ensemble distribution to describe steady immiscible two-phase flow of two incompressible fluids in a porous medium. The system is found to be ergodic. The distribution is used to compute macroscopic flow ...

    • An ensemble framework for identifying essential proteins 

      Zhang, Xue; Xiao, W; Acencio, Marcio Luis; Lemke, Ney; Wang, X (Peer reviewed; Journal article, 2016)
      Many centrality measures have been proposed to mine and characterize the correlations between network topological properties and protein essentiality. However, most of them show limited prediction accuracy,and the number ...

    • Ensemble machine learning based driving range estimation for real‐world electric city buses by considering battery degradation levels 

      Wang, Yongxing; Lu, Chaoru; Bi, Jun; Sai, Qiuyue; Zhang, Yongzhi (Peer reviewed; Journal article, 2021)
      Battery electric buses (BEBs) have been regarded as effective options to address the congestion and pollution problems in the field of urban transportation. However, since the limited driving range of BEBs brings challenges ...

    • An ensemble modelling approach for spatiotemporally explicit estimation of fish distributions using data assimilation 

      Kelly, Cian; Michelsen, Finn Are; Alver, Morten Omholt (Journal article; Peer reviewed, 2023)
      This article presents a novel method for estimating large scale spatiotemporal distribution patterns of fish populations modelled at the individual level. A single realization of an individual-based model calibrated on ...

    • Ensemble of PANORAMA-based convolutional neural networks for 3D model classification and retrieval 

      Sfikas, Konstantinos; Pratikakis, Ioannis; Theoharis, Theoharis (Journal article; Peer reviewed, 2018)
      A novel method for the classification and retrieval of 3D models is proposed; it exploits the 2D panoramic view representation of 3D models as input to an ensemble of convolutional neural networks which automatically compute ...

    • Ensemble updating of binary state vectors by maximising the expected number of unchanged components 

      Loe, Margrethe Kvale; Tjelmeland, Håkon (Peer reviewed; Journal article, 2020)
      The main challenge in ensemble-based filtering methods is the updating of a prior ensemble to a posterior ensemble. In the ensemble Kalman filter (EnKF), a linear-Gaussian model is introduced to overcome this issue, and ...

    • Ensemble updating of categorical state vectors 

      Loe, Margrethe Kvale; Tjelmeland, Håkon (Peer reviewed; Journal article, 2022)
      An ensemble updating method for categorical state vectors is proposed. The method is based on a Bayesian view of the ensemble Kalman filter (EnKF). In the EnKF, Gaussian approximations to the forecast and filtering ...

    • Ensemble-based seismic inversion for a stratified medium 

      Gineste, Michael; Eidsvik, Jo; Zheng, York (Peer reviewed; Journal article, 2020)
      Seismic waveform inversion is a nontrivial optimization task, which is often complicated by the nonlinear relationship between the elastic attributes of interest and the large amount of data obtained in seismic experiments. ...