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

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    • Effects of compliant and structural parts in evolved modular robots 

      Norstein, Emma Stensby; Veenstra, Frank; Ellefsen, Kai Olav; Nygaard, Tønnes; Glette, Kyrre (Chapter; Peer reviewed; Conference object, 2023)
      A striking difference between animals and traditional robots is that the latter usually have rigid and non-flexible bodies. Animals, on the other hand, exhibit highly adapted traits, such as elastic tendons. The tendons ...

    • Identification of Vibration Frequencies of Railway Bridges from Train-Mounted Sensors Using Wavelet Transformation 

      Erduran, Emrah; Pettersen, Fredrik Marøy; Gonen, Semih; Lau Leong Lee, Albert (Peer reviewed; Journal article, 2023)
      This article presents a novel methodology to extract the bridge frequencies from the vibrations recorded on train-mounted sensors. Continuous wavelet transform is used to distinguish the bridge frequencies from the other ...

    • TRANSQLATION: TRANsformer-based SQL RecommendATION 

      Tahmasebi, Shirin; Payberah, Amir H.; Soylu, Ahmet; Roman, Dumitru; Matskin, Mihhail (IEEE International Conference on Big Data;, Chapter; Peer reviewed; Conference object, 2023)
      The exponential growth of data production emphasizes the importance of database management systems (DBMS) for managing vast amounts of data. However, the complexity of writing Structured Query Language (SQL) queries requires ...

    • A DISCUSSION TO LEARN ABOUT SUSTAINABLE WELFARE SYSTEMS FUNCTIONING 

      Blaasvær, Linda; Gulden, Tore (Chapter, 2023)
      A typical approach when designing a system for social service functioning in the European and Norwegian contexts is to emphasize what does not function—i.e., one does not ask for reasons behind the existence of conforming ...

    • Literal-Aware Knowledge Graph Embedding for Welding Quality Monitoring 

      Tan, Zhipeng; Zheng, Zhuoxun; Klironomos, Antonis; Gad-Elrab, Mohamed H.; Xiao, Guohui; Soylu, Ahmet; Kharlamov, Evgeny; Zhou, Baifan (Peer reviewed; Journal article, 2023)
      Recently there has been a series of studies in knowledge graph embedding (KGE), which attempts to learn the embeddings of the entities and relations as numerical vectors and mathematical mappings via machine learning (ML). ...

    • Semantic Cloud System for Scaling Data Science Solutions for Welding at Bosch 

      Zheng, Zhuoxun; Zhou, Baifan; Tan, Zhipeng; Savkovic, Ognjen; Rincon-Yanez, Diego; Nikolov, Nikolay Vladimirov; Roman, Dumitru; Soylu, Ahmet; Kharlamov, Evgeny (Peer reviewed; Journal article, 2023)
      Background and Challenges. Industry 4.0 focuses on smart factories that rely on IoT tech- nology for automation. This produces massive amounts of production data, increasing the demand for data-driven solutions and cloud ...

    • Datalog with External Machine Learning Functions for Automated Cloud Resource Configuration 

      Zheng, Zhuoxun; Savkovic, Ognjen; Phuc Luu, Huu; Soylu, Ahmet; Kharlamov, Evgeny; Zhou, Baifan (Peer reviewed; Journal article, 2023)
      Industry 4.0 and Internet of Things (IoT) technologies unlock unprecedented amount of data from factory production, posing big data challenges. In that context, distributed computing solutions such as cloud systems are ...

    • Evolution of linkages for prototyping of linkage based robots 

      Norstein, Emma Stensby; Ellefsen, Kai Olav; Veenstra, Frank; Nygaard, Tønnes; Glette, Kyrre (IEEE Symposium Series on Computational Intelligence (SSCI);, Chapter; Peer reviewed; Conference object, 2023)
      Prototyping robotic systems is a time consuming process. Computer aided design, however, might speed up the process significantly. Quality-diversity evolutionary approaches optimise for novelty as well as performance, and ...

    • COCO: an annotated Twitter dataset of COVID-19 conspiracy theories 

      Langguth, Johannes; Schroeder, Daniel Thilo; Filkukova, Petra; Brenner, Stefan; Phillips, Jesper; Pogorelov, Konstantin (Peer reviewed; Journal article, 2023)
      The COVID-19 pandemic has been accompanied by a surge of misinformation on social media which covered a wide range of different topics and contained many competing narratives, including conspiracy theories. To study such ...

    • A Taxonomy for Cloud Storage Cost 

      Khan, Akif Quddus; Nikolov, Nikolay Vladimirov; Matskin, Mihhail; Prodan, Radu; Bussler, Christoph; Roman, Dumitru; Soylu, Ahmet (Communications in Computer and Information Science (CCIS);, Chapter; Peer reviewed; Conference object; Journal article, 2024)
      The cost of using cloud storage services is complex and often an unclear structure, while it is one of the important factors for organisations adopting cloud storage. Furthermore, organisations take advantage of multi-cloud ...

    • Container-Based Data Pipelines on the Computing Continuum for Remote Patient Monitoring 

      Nikolov, Nikolay Vladimirov; Solberg, Arnor; Prodan, Radu; Soylu, Ahmet; Matskin, Mihhail; Roman, Dumitru (Computer;, Peer reviewed; Journal article, 2023)
      Diagnosing, treatment, and follow-up care of patients is happening increasingly through telemedicine, especially in remote areas where direct interaction is hindered. Over the past three years, following the COVID-19 ...

    • 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, ...