• A Review of the State-of-the-Art of Sensing and Actuation Technology for Robotic Grasping and Haptic Rendering 

  Moosavi, Syed Kumayl Raza; Zafar, Muhammad Hamza; Sanfilippo, Filippo (Chapter, 2022)

  In this paper, a survey of the state of the art, chal-lenges, and possibilities with sensing and actuation technology for robotic grasping and haptic rendering is presented. To this end, a survey and classification of ...

• A Convolutional Tsetlin Machine-based Field Programmable Gate Array Accelerator for Image Classification 

  Tunheim, Svein Anders; Lei, Jiao; Shafik, Rishad; Yakovlev, Alex; Granmo, Ole-Christoffer (Chapter, 2022)

  This paper presents a Field Programmable Gate Array (FPGA) implementation of an image classification accelerator based on the Convolutional Tsetlin Machine (CTM). The work is a concept design, and the solution demonstrates ...

• Diagnosis of Sensor Faults in PMSM and Drive System Based on Structural Analysis 

  Ebrahimi, Saeed Hasan; Choux, Martin Marie Hubert; Huynh, Khang (Chapter; Peer reviewed, 2021)

  Virtual reality promises to be a tool that can improve higher education. Immersive virtual environments offer the chance to enrich courses with experiential learning experiences. The technological possibilities evolve ...

• On the Convergence of Tsetlin Machines for the XOR Operator 

  Lei, Jiao; Zhang, Xuan; Granmo, Ole-Christoffer; Abeyrathna, Kuruge Darshana (Peer reviewed; Journal article, 2022)

  The Tsetlin Machine (TM) is a novel machine learning algorithm with several distinct properties, including transparent inference and learning using hardware-near building blocks. Although numerous papers explore the TM ...

• Recent Advances and Future Directions of Microwave Photonic Radars: A Review 

  Panda, Saran Srihari Sripada; Panigrahi, Trilochan; Parne, Saidi Reddy; Sabat, Samrat L.; Cenkeramaddi, Linga Reddy (Journal article; Peer reviewed, 2021)

  Microwave photonic (MWP) radar has the advantages of generating and processing wide bandwidth microwave signals, reconfigurability, high immunity to electromagnetic interference compared to microwave electronic radar. It ...

• Comparative Analysis of Machine Learning and Large Language Models for Evaluating Customer Feedback and Reviews in Telecommunication Services 

  Thantharate, Aayushi (Master thesis, 2024)

  In the present era, reviews and personal recommendations play a significant role in guiding people’s decision-making processes. A fundamental task within natural language processing, sentiment analysis involves anticipation ...

• Entrepreneurs' Responses to Crises 

  KONGOLO, CALEB; YOHANNES, BENHUR (Master thesis, 2024)

  A quantitative study exploring both theoretical and practical perspectives on entrepreneurial crisis.

• A Trajectory-Driven SISO mm-Wave Channel Model for a Human Activity Recognition 

  Avazov, Nurilla; Hicheri, Rym; Pätzold, Matthias Uwe (Chapter, 2021)

  In this paper, we propose a trajectory-driven three-dimensional (3D) non-stationary channel model for millimeter wave (mm-Wave) single-input single-output (SISO) systems. The proposed channel model is designed to model and ...

• Frequency-domain experimental setup for mechatronic and suspension system components 

  Tavares, Rafael Pinto; Ruderman, Michael (Chapter, 2021)

  This paper presents a frequency-domain experimental setup for modal analysis of mechatronic and suspension system components. Design, instrumentation and dynamic behavior of the one degree-of-freedom (DOF) system, capable ...

• Measuring the Novelty of Natural Language Text using the Conjunctive Clauses of a Tsetlin Machine Text Classifier 

  Bhattarai, Bimal; Granmo, Ole-Christoffer; Jiao, Lei (Chapter, 2021)

  Most supervised text classification approaches assume a closed world, counting on all classes being present in the data at training time. This assumption can lead to unpredictable behaviour during operation, whenever novel, ...

• Sustainable approach to teaching embedded systems with hands-on project-based visible learning 

  Sanfilippo, Filippo; Austreng, Kolbjørn (Peer reviewed; Journal article, 2021)

  Although purchasing state-of-the-art teaching equipment may be financially demanding, substantial efforts are being made at the Norwegian University of Science and Technology (NTNU) in Trondheim to provide students with ...

• Teaching Students to Think Mathematically Through Inquiry: The Norwegian Experience 

  Rogovchenko, Svitlana; Rogovchenko, Yuriy (Chapter, 2021)

• Emergency Detection with Environment Sound Using Deep Convolutional Neural Networks 

  Sharma, Jivitesh; Granmo, Ole-Christoffer; Goodwin, Morten (Chapter, 2020)

  In this paper we propose a generic emergency detection system using only the sound produced in the environment. For this task, we employ multiple audio feature extraction techniques like the Mel-Frequency Cepstral Coefficients, ...

• Modeling and Analysis of Flexible Bodies Using Lumped Parameter Method 

  Subedi, Dipendra; Tyapin, Ilya; Hovland, Geir (Chapter, 2020)

  The modeling, identification and analysis of a flexible beam is presented. The lumped parameter method is used to model a flexible beam. The use of camera measurements to identify lumped parameters, namely spring stiffness ...

• ConvTextTM: An Explainable Convolutional Tsetlin Machine Framework for Text Classification 

  Bhattarai, Bimal; Granmo, Ole-Christoffer; Lei, Jiao (Chapter, 2022)

  Recent advancements in natural language processing (NLP) have reshaped the industry, with powerful language models such as GPT-3 achieving superhuman performance on various tasks. However, the increasing complexity of such ...

• Large surface magnetization in noncentrosymmetric antiferromagnets 

  Lund, Mike Alexander; Everschor-Sitte, Karin; Hals, Kjetil Magne Dørheim (Peer reviewed; Journal article, 2020)

  Thin-film antiferromagnets (AFs) with Rashba spin-orbit coupling are theoretically investigated. We demonstrate that the relativistic Dzyaloshinskii-Moriya interaction (DMI) produces a large surface magnetization and a ...

• Developing Fracture-Based Fragility Curves for Steel Components in Corrosive Environments 

  Mahdavipour, Mohammad Ali; Vysochinskiy, Dmitry (Journal article; Peer reviewed, 2022)

  Under excessive plastic deformations, pitting corrosion accelerates ductile fracture initiation in steel components. Because of the stochastic and time-dependent nature of corrosion in steel material, the integrity of the ...

• Sleep Monitoring with Wearable Sensor Data in an eCoach Recommendation System: A Conceptual Study with Machine Learning Approach 

  Chatterjee, Ayan; Prinz, Andreas; Pahari, Nibedita; Das, Jishnu; Riegler, Michael (Lecture Notes in Networks and Systems; no. 519, Chapter; Peer reviewed, 2023)

  The collective effects of sleep loss and sleep disorders are correlated with many adverse health consequences, including increased risk of high blood pressure, obesity, diabetes, depressive state, and cardiovascular symptoms. ...

• Creating Renewable Energy and Energy Efficiency Awareness: A Case Study on a Public Energy Awareness Campaign 

  Berntzen, Lasse; Johannessen, Marius Rohde; Isarie, Claudiu; Rotaru, Mihaela (Article; Peer reviewed, 2024)

  This paper presents the outcomes of the collaborative project "Renewable Energy and Energy Efficiency for Sustainable Development in Sibiu County," conducted jointly by Sibiu County, Romania, Lucian Blaga University of ...

• Towards a deep reinforcement learning approach for Tower Line Wars 

  Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (Lecture Notes in Artificial Intelligence (LNAI), Journal article; Peer reviewed, 2017)

  There have been numerous breakthroughs with reinforcement learning in the recent years, perhaps most notably on Deep Reinforcement Learning successfully playing and winning relatively advanced computer games. There is ...

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