Scientific Publications in Information and Communication Technology
Recent Submissions
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Smart load prediction analysis for distributed power network of Holiday Cabins in Norwegian rural area
(Peer reviewed; Journal article, 2020)The Norwegian rural distributed power network is mainly designed for Holiday Cabins with limited electrical loading capacity. Load prediction analysis, within such type of network, is necessary for effective operation and ... -
Distributed Resource Allocation in Underlay Multicast D2D Communications
(Peer reviewed; Journal article, 2021)Multicast device-to-device communications operating underlay with cellular networks is a spectral efficient technique for disseminating data to nearby receivers. However, due to the critical challenge of having an intelligent ... -
A Convolutional Tsetlin Machine-based Field Programmable Gate Array Accelerator for Image Classification
(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 ... -
On the Convergence of Tsetlin Machines for the XOR Operator
(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
(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 ... -
Measuring the Novelty of Natural Language Text using the Conjunctive Clauses of a Tsetlin Machine Text Classifier
(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, ... -
Emergency Detection with Environment Sound Using Deep Convolutional Neural Networks
(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, ... -
ConvTextTM: An Explainable Convolutional Tsetlin Machine Framework for Text Classification
(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 ... -
Sleep Monitoring with Wearable Sensor Data in an eCoach Recommendation System: A Conceptual Study with Machine Learning Approach
(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. ... -
Towards a deep reinforcement learning approach for Tower Line Wars
(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 ... -
Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games
(Chapter, 2018)Reinforcement learning (RL) is an area of research that has blossomed tremendously in recent years and has shown remarkable potential for artificial intelligence based opponents in computer games. This success is primarily ... -
Learning Environments in the 21st Century: A Mapping of the Literature
(Chapter; Peer reviewed, 2020)Education has been transformed by significant breakthroughs in AI, mobile internet, cloud computing and Big Data technologies. More personalized educational settings are developed by increasingly integrating contemporary ... -
Lightweight deep convolutional neural network for background sound classification in speech signals
(Journal article; Peer reviewed, 2022)Recognizing background information in human speech signals is a task that is extremely useful in a wide range of practical applications, and many articles on background sound classification have been published. It has not, ... -
Towards Routinely Using Virtual Reality in Higher Education
(Chapter; Peer reviewed, 2022)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 ... -
ConvTextTM: An Explainable Convolutional Tsetlin Machine Framework for Text Classification
(Journal article, 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 ... -
Radar-Based Passive Step Counter and Its Comparison with a Wrist-Worn Physical Activity Tracker
(Communications in Computer and Information Science (CCIS); no. 1616, Chapter; Peer reviewed, 2022)Inspired by novel applications of radio-frequency sensing in healthcare, smart homes, rehabilitation, and augmented reality, we present an FMCW radar-based passive step counter. If a person walks or performs other activities, ... -
Localization and Activity Classification of Unmanned Aerial Vehicle using mmWave FMCW Radars
(Peer reviewed; Journal article, 2021)In this article, we present a novel localization and activity classification method for aerial vehicle using mmWave frequency modulated continuous wave (FMCW) Radar. The localization and activity classification for aerial ... -
Target Classification by mmWave FMCW Radars using Machine Learning on Range-Angle Images
(Peer reviewed; Journal article, 2021)In this paper, we present a novel multiclass-target classification method for mmWave frequency modulated continuous wave (FMCW) radar operating in the frequency range of 77 - 81 GHz, based on custom range-angle heatmaps ... -
Rate-Splitting Random Access Mechanism for Massive Machine Type Communications in 5G Cellular Internet-of-Things
(Chapter, 2021)The cellular Internet-of-Things has resulted in the deployment of millions of machine type communication (MTC) devices under the coverage of a single gNodeB (gNB). These massive number of devices should connect to the ...
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