Department of Electrical and Computer Engineering (TN-IDE): Nye registreringer

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    • Rate of Penetration (ROP) Optimization through Data-Driven Approach 

      Adnan, Isar (Master thesis, 2023)
      One method to lower cost and Non-Productive Time (NPT) in drilling wells is to achieve the highest rate of penetration (ROP). ROP is influenced by a variety of factors, including tooth attrition and hole cleaning. Three ...

    • Simulating Swarm's storage incentive 

      Tjessem, Kristian Horve (Master thesis, 2023)
      Swarm is a decentralized storage platform consisting of several independently operated nodes. The nodes store data units called chunks. Storing chunks allows them to partake in Swarm's storage incentive. The storage incentive ...

    • A Federated Computational Workflow for Analysis of DISKOS Digital Palynological Slides 

      Udegbunam, John Emeka; Gonzalez, Reynel Isaac Villabona (Master thesis, 2023)
      A novel federated computational workflow for analyzing digital palynological slide images is implemented in this thesis. The slide data files, typically exceeding 3GB, present significant data mobility and computation ...

    • Health Index Estimation and RUL Prediction on Gear Pumps 

      Henrik Skulevold (Master thesis, 2023)
      This thesis explores innovative machine learning and signal processing techniques to accurately estimate the wear by constructing Health Indexes and predict the Remaining Useful Life (RUL) of gear pumps used in ABB Robotics’ ...

    • Real-time latency regression testing with extreme value theory 

      Olsen, Sander Låstad (Master thesis, 2023)
      This paper creates a regression testing system for real-time latency data measured using cyclictest and hackbech, and uses extremem value theory (block maxima, specifically) to compute an acceptable lower and upper bound ...

    • Improved automatic testing of events on robot-path measurements used in robots 

      Gundersen, Alide (Master thesis, 2023)
      This master’s thesis investigates the activation time of electrical signals along a robot’s path and explores the potential impact of calculation errors in robot position and speed. The study emphasizes the need for reliable ...

    • Rask Policy-Læring Gjennom Imitation Learning og Reinforcement Learning i Løfteoperasjoner 

      Liebert, Robin; Yurchenko, Yuriy (Master thesis, 2023)
      I denne forskningen ble implementering og evaluering av en ny læringsmetode for autonom kranoperasjon kalt LOKI-G (Locally Optimal search after K-step Imitation - Generalized) ved hjelp av Closed-form Continous-time (CfC) ...

    • Bruk av ekstern sensor for å korrigere robotbane i sanntid 

      Thorkildsen, Erlend Ettersti (Master thesis, 2023)
      This master thesis investigates the feasibility of using ABB's Externally Guided Motion (EGM) with path correction to adjust a pre-programmed robot path in real-time. The research explores whether the EGM controller, along ...

    • Videreutvikling av 3D selvredningsspill for tunnelbrann 

      Søberg, Jesper; Tysdal, Magnus; Kase, Simen G. (Bachelor thesis, 2023)
      Denne avhandlingen presenterer et system som gir tilgang til dataene i Nasjonal Vegdatabank (NVDB) for en spill-simulering av en tunnel. De primære målene var å skape en mer realistisk spillopplevelse, ved å gjøre tunnelen ...

    • An Emulation Framework for Evaluating V2X Communications in C-ITS Applications 

      Essandoh Raymond (Master thesis, 2023)
      C-ITS enhances transportation systems with advanced communication tech, enabling vehicle-to-vehicle and vehicle-to-infrastructure data exchange for real-time decision-making. The thesis explores C-ITS concepts, DSRC, and ...

    • Tunnel Traffic Forecasting Using Deep Learning 

      Riaz, Aman (Master thesis, 2023)
      Tunnel traffic congestion can increase the risk of traffic accidents, tunnel fires, and environmental effect. Despite numerous studies on traffic forecasting using deep learning, research on tunnel traffic remains ...

    • Automated Fact-Checking of Podcasts 

      Becker, Adam James (Master thesis, 2023)
      Podcasts have gone mainstream and continue to attract ever larger audiences, particularly among younger demographics, while the internet-broadcast nature of the medium leaves listeners with little recourse in the face of ...

    • A Deep Learning Approach to Generating Human Faces in 3D Media 

      Carlsson, Tor Håkon (Master thesis, 2023)
      This paper proposes new machine learning architectures for generating face meshes that can be used in 3D media. They are based on the architecture introduced in "pix2pix: Image-to-image translation with a conditional GAN". ...

    • Detection of MITM using AI 

      Fernandez, Alistar Thomas Cyril (Master thesis, 2023)
      In the current digital era, there is a rising need for interconnected networks and communication systems, which raises the risk of cyberattacks, notably the Man-in-the-Middle (MitM) attack. An adversary intercepts and ...

    • Security-aware Resource Allocation for Space-Air-Ground Integrated Network using Deep Reinforcement Learning 

      Netteland, Fredrik (Master thesis, 2023)
      A Space-Air-Ground Integrated Network (SAGIN) has been proposed to extend communication network service coverage to consumer-oriented and industrial sectors where communication network coverage is either limited or ...

    • Resource Allocation for Vertical Industries in a Smart City Using Deep Reinforcement Learning 

      Riis Gundersen, Brage (Master thesis, 2023)
      This Master’s thesis addresses the problem of resource allocation in Network Function Virtualization (NFV) within the context of a smart city considering isolation. The objective of the thesis is to minimize the long-term ...

    • Frontal-Profile Face Recognition Using Deep Learning Algorithms 

      Karimi Mahboubeh (Master thesis, 2023)
      This study investigates the impact of pose variation, particularly extreme poses such as the profile view, on the performance of biometric recognition systems. The study employs the Local Binary Pattern (LBP) approach in ...

    • A Machine Learning approach for Building Segmentation using laser data 

      Finnesand, Erik (Master thesis, 2023)
      Buildings are essential for population information, city management, and policy-making. Various computer vision technologies have proven helpful in building-related scenarios, where segmentation has proven to be the most ...

    • Comparative Analysis of Sampling Methods for Imbalanced Classification 

      Koloszyc Piotr; Li Rongbing (Master thesis, 2023)
      Assigning class labels to instances is a key component of the machine learning technique known as classification predictive modeling. While concentrating largely on balanced classification problems, which are thought to ...

    • Comparative Analysis of Sampling Methods for Imbalanced Classification 

      Li, Rongbing; Koloszyc, Piotr (Master thesis, 2023)
      Assigning class labels to instances is a key component of the machine learning technique known as classification predictive modeling. While concentrating largely on balanced classification problems, which are thought to ...