Now showing items 294-313 of 561

    • Large scale integration of wireless sensor network technologies for air quality monitoring at a logistics shipping base 

      Molka-Danielsen, Judith; Engelseth, Per; Wang, Hao (Journal article; Peer reviewed, 2018)
      The future of logistics shipping bases will be to seek efficient flows of materials to meet the needs of business partners. Supply chain and operations managers of supply bases will need to integrate technologies that allow ...
    • Laser assisted optical gap detection 

      Mjåland, Thomas; Strand, Sigurd (Bachelor thesis, 2019)
      Utvikling av et system for å detektere gap/skillet mellom pakker i et varehus ved hjelp av line-laser og kamera.
    • Laststyring for å redusere nettbelastning 

      Humlen, Fredrik; Samset, Einar (Bachelor thesis, 2021)
      I denne bacheloroppgaven blir det undersøkt løsninger for å redusere effekttopper i strømforbruket til forskjellige bygg. Oppgaven er gitt av Norconsult. De har bistått med informasjon som gjør at det kunne ses på løsninger ...
    • Learning cost function for graph classification with open-set methods 

      Werneck, Rafael de Oliveira; Raveaux, Romain; Tabbone, Salvatore; Torres, Ricardo Da Silva (Journal article; Peer reviewed, 2019)
      In several pattern recognition problems, effective graph matching is of paramount importance. In this paper, we introduce a novel framework to learn discriminative cost functions. These cost functions are embedded into a ...
    • Learning the Morphological and Syntactic Grammars for Named Entity Recognition 

      Sun, Mengtao; Yang, Qiang; Wang, Hao; Pasquine, Mark; Hameed, Ibrahim A. (Journal article; Peer reviewed, 2022)
      In some languages, Named Entity Recognition (NER) is severely hindered by complex linguistic structures, such as inflection, that will confuse the data-driven models when perceiving the word’s actual meaning. This work ...
    • Learning Vocabularies to Embed Graphs in Multimodal Rank Aggregation Tasks 

      Dourado, Icaro; Torres, Ricardo Da Silva (Chapter, 2021)
      This paper introduces Supervised Bag of Graphs (SBoG), a supervised vocabulary learning approach for multi-modal graph-based rank aggregation tasks. In our formulation, collection objects are represented based on complementary ...
    • Leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: A Norwegian case study 

      Muhammad, Umair Hassan; Saleh, A.; Raheem, Sawar; Raheel, Nawaz; Hameed, Ibrahim A. (Journal article; Peer reviewed, 2023)
      Computer science graduates face a massive gap between industry-relevant skills and those learned at school. Industry practitioners often counter a huge challenge when moving from academics to industry, requiring a completely ...
    • Leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: A Norwegian case study 

      Hassan, Muhammad Umair; Alaliyat, Saleh Abdel-Afou; Sarwar, Raheem; Nawaz, Raheel; Hameed, Ibrahim A (Peer reviewed; Journal article, 2023)
      Computer science graduates face a massive gap between industry-relevant skills and those learned at school. Industry practitioners often counter a huge challenge when moving from academics to industry, requiring a completely ...
    • Light Column System 

      Hagen, Gustav Sørdal; Buljo, Ole Jørgen Klemetsen; Alvestad, Per-Stian (Bachelor thesis, 2021)
      Denne oppgaven består av forskning og utvikling av et Lyskolonne System (LCS) for Vard Electro AS. LCS er en samling av lyd- og optisk varslingssystem for alarmer om bord i fartøy, og er plassert i bråkete områder av ...
    • Line follower robot 

      Boge, Sander Sæther; Bostad, Kjell Christian Rørvik; Lund, Rolf Helge (Bachelor thesis, 2023)
      Dette prosjektet omfattet utviklingen og forbedringen av en autonom linjefølgende robot for deltakelse i Latvian Robot Competition. Roboten konkurrerte i Latvian Robot Competition. For å kunne konkurrere ble teknikker som ...
    • Link Connectivity and Coverage of Underwater Cognitive Acoustic Networks under Spectrum Constraint 

      Wang, Qiu; Dai, Hong-Ning; Cheang, Chak Fong; Wang, Hao (Journal article; Peer reviewed, 2017)
      Extensive attention has been given to the use of cognitive radio technology in underwater acoustic networks since the acoustic spectrum became scarce due to the proliferation of human aquatic activities. Most of the recent ...
    • Linking partnering success factors to project performance - Findings from two nation-wide surveys 

      Nevstad, Kristina; Madsen, Tage Koed; Eskerod, Pernille; Aarseth, Wenche Kristin; Karlsen, Anniken Th; Andersen, Bjørn Sørskot (Peer reviewed; Journal article, 2021)
      In this article we present findings from an investigation into the influence of partnering success factors on multi-partner projects’ abilities to meet time schedule, budget, and technical specifications. Our findings are ...
    • Litter Detection with Deep Learning: A Comparative Study 

      Cordova, Manuel; Pinto, Allan; Hellevik, Christina Carrozzo; Alaliyat, Saleh Abdel-Afou; Hameed, Ibrahim A.; Pedrini, Helio; Torres, Ricardo da S. (Peer reviewed; Journal article, 2022)
      Pollution in the form of litter in the natural environment is one of the great challenges of our times. Automated litter detection can help assess waste occurrences in the environment. Different machine learning solutions ...
    • Load Frequency Control and Automatic Voltage Regulation in a Multi-Area Interconnected Power System Using Nature-Inspired Computation-Based Control Methodology 

      Ali, Tayyab; Malik, Suheel Abdullah; Hameed, Ibrahim A.; Daraz, Amil; Mujlid, Hana; Azar, Ahmad Taher (Peer reviewed; Journal article, 2022)
      The stability control of nominal frequency and terminal voltage in an interconnected power system (IPS) is always a challenging task for researchers. The load variation or any disturbance affects the active and reactive ...
    • Location of obecjt with help of sound triangulation 

      Skåra Simen Hansen; Litwicki Dawid; Brabrand Trym (Bachelor thesis, 2023)
      Kongsberg Maritime has expressed interest in using sound to automate boat location tracking. The bachelor group is entrusted with doing research into efficient ways to carry out this. The thesis will simulate a boat that ...
    • Lyskolonne 

      Kjerstad,Johann; Sandøy, Simon (Bachelor thesis, 2019)
      Vard Electro AS er en av verdens største selskaper innenfor spesialiserte fartøy. Med sin maritime kompetanse tilbyr de høyteknologiske teknologiske løsninger. Blant annet installerer de alarmsystemer. Disse er bygget som ...
    • A Machine Learning and Blockchain Based Efficient Fraud Detection Mechanism 

      Ashfaq, Tehreem; Khalid, Rabiya; Yahaya, Adamu Sani; Aslam, Sheraz; Azar, Ahmad Taher; Alsafari, Safa; Hameed, Ibrahim A. (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 for Automatically Counting Growth-Stunted Fish in Sea Cages 

      Sperre, Linda Helen (Master thesis, 2023)
      Lakseoppdrettsmerder inneholder ofte et stort antall veksthindrede fisk omtalt som "taperfisk". Tilstedeværelsen av taperfisk kan indikere utilstrekkelige velferdsfaktorer eller sykdommer. Ved å overvåke forekomsten av ...
    • A Machine Learning-Based Model for Stability Prediction of Decentralized Power Grid Linked with Renewable Energy Resources 

      Ibrar, Muhammad; Hassan, Muhammad Awais; Shaukat, Kamran; Alam, Talha Mahboob; Khurshid, Khaldoon Syed; Hameed, Ibrahim A.; Aljuaid, Hanan; Luo, Suhuai (Peer reviewed; Journal article, 2022)
      A decentralized power grid is a modern system that implements demand response without requiring major infrastructure changes. In decentralization, the consumers regulate their electricity demand autonomously based on the ...
    • Machine Translation in Low-Resource Languages by an Adversarial Neural Network 

      Sun, Mengtao; Wang, Hao; Pasquine, Mark; Abdelfattah Abdelhameed, Ibrahim (Peer reviewed; Journal article, 2021)
      Existing Sequence-to-Sequence (Seq2Seq) Neural Machine Translation (NMT) shows strong capability with High-Resource Languages (HRLs). However, this approach poses serious challenges when processing Low-Resource Languages ...