Fakultet for teknologi, kunst og design (TKD): Nye registreringer

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    • Direct Numerical Simulations of Turbulent Flow in Helical Pipes 

      Lupi, V.; Örlü, Ramis; Schlatter, P. (ERCOFTAC Series;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Direct numerical simulations of the fully developed turbulent flow through helical pipes are performed. The numerical procedure is described, and a validation of the volume force driving the flow is presented. A comparison ...

    • Enhancing investigative interview training using a child avatar system: a comparative study of interactive environments 

      Zohaib Hassan, Syed; Shafiee Sabet, Saeed; Riegler, Michael Alexander; Baugerud, Gunn Astrid; Ko, Hayley Manalang; Salehi, Pegah; Røed, Ragnhild Klingenberg; Sinkerud Johnson, Miriam; Halvorsen, Pål (Peer reviewed; Journal article, 2023)
      The impact of investigative interviews by police and Child Protective Services (CPS) on abused children can be profound, making effective training vital. Quality in these interviews often falls short and current training ...

    • Phonon Transport Characteristics of Nano-Silicon Thin Films Irradiated by Ultrafast Laser under Dispersion Relation 

      Mao, Yudong; Liu, Shouyu; Liu, Jiying; Yu, Mingzhi; Li, Xinwei; Kim, Moon Keun; Yang, Kaimin (Peer reviewed; Journal article, 2024)
      The gray model simplifies calculations by ignoring phonon polarization, but sacrifices a certain level of computational accuracy. In effect, the frequency and wavevector of phonons form complex polarization patterns, which ...

    • Flow resistance over heterogeneous roughness made of spanwise-alternating sandpaper strips 

      Frohnapfel, B.; von Deyn, L. H.; Yang, J.; Neuhauser, J.; Stroh, A.; Örlü, Ramis; Gatti, D. (Peer reviewed; Journal article, 2024)
      The Reynolds number dependent flow resistance of heterogeneous rough surfaces is largely unknown at present. The present work provides novel reference data for spanwise-alternating sandpaper strips as one idealised case ...

    • Predicting disease severity in multiple sclerosis using multimodal data and machine learning 

      Andorra, Magi; Freire, Ana; Zubizarreta, Irati; de Rosbo, Nicole Kerlero; Bos, Steffan Daniel; Rinas, Melanie; Høgestøl, Einar August; de Rodez Benavent, Sigrid Aune; Berge, Tone; Brune, Synne; Ivaldi, Federico; Cellerino, Maria; Pardini, Matteo; Vila, Gemma; Pulido-Valdeolivas, Irene; Martinez-Lapiscina, Elena H.; Llufriu, Sara; Saiz, Albert; Blanco, Yolanda; Martinez-Heras, Eloy; Solana, Elisabeth; Bäcker-Koduah, Priscilla; Behrens, Janina; Kuchling, Joseph; Asseyer, Susanna; Scheel, Michael; Chien, Claudia; Zimmermann, Hanna; Motamedi, Seyedamirhosein; Kauer-Bonin, Josef; Brandt, Alex; Saez-Rodriguez, Julio; Alexopoulos, Leonidas G.; Paul, Friedemann; Harbo, Hanne-Cathrin Flinstad; Shams, Hengameh; Oksenberg, Jorge; Uccelli, Antonio; Baeza-Yates, Ricardo; Villoslada, Pablo (Peer reviewed; Journal article, 2023)
      Background Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity. Methods We have analysed a prospective ...

    • Limitations and Opportunities in PHM for Offshore Wind Farms: A Socio-Technical-Ecological System Perspective 

      Keprate, Arvind (Chapter, 2023)
      The burgeoning importance of offshore wind farms (OWFs) in the transition to sustainable energy systems underscores the need for effective Prognostics and Health Management (PHM) strategies. While the current PHM framework ...

    • Comparing Deep Learning Based Image Processing Techniques for Unsupervised Anomaly Detection in Offshore Wind Turbines 

      Keprate, Arvind; Sheikhi, Saeid; Siddiqui, Muhammad Salman (IEEE International Conference on Industrial Engineering and Engineering Management;, Chapter; Peer reviewed; Conference object, 2023)
      Offshore wind turbines (OWTs) play a crucial role in renewable energy generation, but their remote and harsh environments make them prone to various anomalies that can significantly affect their performance and reliability. ...

    • Exploring value dilemmas of brain monitoring technology through speculative design scenarios 

      Risnes, Martha; Thorstensen, Erik; Mirtaheri, Peyman; Berg, Arild Skarsfjord (Peer reviewed; Journal article, 2024)
      In the field of brain monitoring, the advancement of more user-friendly wearable and non-invasive devices is introducing new opportunities for application outside the lab and clinical use. Despite the growing importance ...

    • From Theory to Practice Leveraging Project Based Learning to Cultivate Student Engagement in Mechanical Engineering Education 

      Keprate, Arvind; Woodford, Sam; Borrajo, Rafael (IEEE International Conference on Industrial Engineering and Engineering Management;, Chapter; Peer reviewed; Conference object, 2024)
      This paper explores the transformative impact of Education 4.0 on learning experiences in the context of mechanical engineering education. Education 4.0 is an evolving paradigm that is student-centered, scalable, ...

    • Measurements in a Turbulent Channel Flow by Means of an LDV Profile Sensor 

      Pasch, S.; Leister, R.; Gatti, D.; Örlü, Ramis; Frohnapfel, B.; Kriegseis, J. (Peer reviewed; Journal article, 2023)
      Spatially and temporally resolved velocity measurements in wall-bounded turbulent flows remain a challenge. Contrary to classical laser Doppler velocimetry (LDV) measurements, the laser Doppler velocity profile sensor ...

    • In-Situ Analysis of Backflow Events and Their Relation to Separation in Wings Through Well-Resolved LES 

      Mallor, F.; Liu, J.; Peplinski, A.; Vinuesa, R.; Örlü, Ramis; Weinkauf, Tino; Schlatter, P. (ERCOFTAC (European Research Community on Flow, Turbulence and Combustion);, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Wall-bounded turbulent flows as those occurring in transportation (e.g. aviation) or industrial applications (e.g turbomachinery), are usually subjected to pressure gradients (PGs). The presence of such PGs affects greatly ...

    • The arts of attention and Oslo Architecture Triennale 

      Sachs Olsen, Cecilie (Peer reviewed; Journal article, 2024)
      This paper starts from a two-fold observation: firstly, that attention rests at the core of our environmental challenges; and secondly, that by becoming (more) attentive to the modified, transformed, and controlled urban ...

    • Household Energy Consumption Prediction: A Deep Neuroevolution Approach 

      Soudaei, Alexander; Zhang, Jianhua; Elmi, Mohamed Ahmed; Tsechoev, Mikael; Khan, Zishan; Osman, Ahmed Abbas (Chapter, 2023)
      Accurate energy consumption prediction can provide insights to make better informed decisions on energy purchase and generation. It also can prevent overloading and make it possible to store energy more efficiently. In ...

    • Embodied eco-embroidery - creative craftsmanship in sustainable STEAM-education 

      Robberstad, Janne Iren; Kvellestad, Randi Veiteberg (Peer reviewed; Journal article, 2023)
      The UN Sustainable Development Goal 4 (SDG4) addresses equal access to quality education, focusing on literacy, numeracy and the science-field STEM subjects (Science, Technology, Engineering, Mathematics), - seemingly ...

    • Geotechnical laboratory testing of lunar simulants and the importance of standardization 

      Quinteros, Santiago; Mikesell, Thomas Dylan; Griffiths, Luke; Jerves, Alex Xavier (Peer reviewed; Journal article, 2024)
      A comprehensive program of geotechnical index tests performed on two regolith simulants, namely LHS-1 and LMS-1, are presented and discussed in this study. The index tests included a 2D analysis of particles shapes ...

    • Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge 

      Ali, Sharib; Ghatwary, Noha; Jha, Debesh; Isik-Polat, Ece; Polat, Gorkem; Yang, Cheng; Li, Wuyang; Galdran, Adrian; Ballester, Miguel Angel Gonzalez; Thambawita, Vajira L B; Hicks, Steven; Poudel, Sahadev; Lee, Sang-Woong; Jin, Ziyi; Gan, Tianyuan; Yu, Chenghui; Yan, JiangPeng; Yeo, Doyeob; Lee, Hyunseok Lee; Tomar, Nikhil Kumar; Haitham, Mahmood; Ahmed, Amr; Riegler, Michael Alexander; Daul, Christian; Halvorsen, Pål; Rittscher, Jens; Salem, Osama E.; Lamarque, Dominique; Cannizzaro, Renato; Realdon, Stefano; de Lange, Thomas; East, James E (Peer reviewed; Journal article, 2024)
      Polyps are well‑known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal ...

    • ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER 

      Layegh, Amirhossein; Hossein Payberah, Amir; Soylu, Ahmet; Roman, Dumitru; Matskin, Mihhail (IEEE Annual International Computer Software and Applications Conference (COMPSAC);, Chapter; Peer reviewed; Conference object, 2023)
      Prompt-based language models have produced encouraging results in numerous applications, including Named Entity Recognition (NER) tasks. NER aims to identify entities in a sentence and provide their types. However, the ...

    • MS Innvik: A Ship with a View – Culture is who we are 

      Bergaust, Kristin (Peer reviewed; Journal article, 2023)
      The video works A Ship with a View and The Kitchen Garden were made during 2010 on the theatre ship MS Innvik, run by Nordic Black Theatre. This turned out to be the last year of the ship’s existence as an intercultural ...

    • Semantic Modeling, Development and Evaluation for the Resistance Spot Welding Industry 

      Yahya, Muhammad; Zhou, Baifan; Breslin, John G.; Ali, Muhammad Intizar; Kharlamov, Evgeny (Peer reviewed; Journal article, 2023)
      The ongoing industrial revolution termed Industry 4.0 (I4.0) has borne witness to a series of profound changes towards increasing smart automation, particularly in the industrial sectors of automotive, aerospace, manufacturing, ...

    • Real-Time Event Detection with Random Forests and Temporal Convolutional Networks for More Sustainable Petroleum Industry 

      Qu, Yuanwei; Zhou, Baifan; Waaler, Arild Torolv Søetorp; Cameron, David B. (Journal article, 2023)
      The petroleum industry is crucial for modern society, but the production process is complex and risky. During the production, accidents or failures, resulting from undesired production events, can cause severe environmental ...