Browsing Department of Electrical and Computer Engineering (TN-IDE) by Author "Wiktorski, Tomasz"
Now showing items 21-29 of 29
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Minimum Word Error Rate Training for Speech Separation
Seo, Jungwon (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06-15)The cocktail party problem, also known as a single-channel multi-talker problem, is a significant challenge to enhance the performance of automatic speech recognition (ASR) systems. Most existing speech separation model ... -
Optimizing support vector machines and autoregressive integrated moving average methods for heart rate variability data correction
Svane, Jakob; Wiktorski, Tomasz; Trygve Christian, Eftestøl; Stein, Ørn (Peer reviewed; Journal article, 2023-09)Heart rate variability (HRV) is the variation in time between successive heartbeats and can be used as an indirect measure of autonomic nervous system (ANS) activity. During physical exercise, movement of the measuring ... -
Predictive Maintenance for Lift Systems in Automated Storage and Retrieval Systems
Matre, Vegard; Øvrebø, Ådne (Master thesis, 2023)This thesis, conducted in partnership with AutoStore, examines the potential of predictive maintenance (PM) in the lift systems of their automated storage and retrieval robots. In the context of Industry 4.0, PM becomes ... -
Recurrent Neural Networks for Artifact Correction in HRV Data During Physical Exercise
Svane, Jakob; Wiktorski, Tomasz; Ørn, Stein; Eftestøl, Trygve Christian (Peer reviewed; Journal article, 2023)In this paper, we propose the use of recurrent neural networks (RNNs) for artifact correction and analysis of heart rate variability (HRV) data. HRV can be a valuable metric for determining the function of the heart and ... -
A Survey on Distributed Fibre Optic Sensor Data Modelling Techniques and Machine Learning Algorithms for Multiphase Fluid Flow Estimation
Arief, Hasan Asyari; Wiktorski, Tomasz; Thomas, Peter (Peer reviewed; Journal article, 2021)Real-time monitoring of multiphase fluid flows with distributed fibre optic sensing has the potential to play a major role in industrial flow measurement applications. One such application is the optimization of hydrocarbon ... -
The application of big data analysis and machine learning for kick detection and kick prediction during drilling operations
Farzad, Maryam (Master thesis, 2021)Drilling operations for oil and gas extraction is a complex and risky process. Workers are not able to start the drilling operations unless they carefully accomplish some pre-drilling activities such as choosing a proper ... -
Training-while-drilling approach to inclination prediction in directional drilling utilizing recurrent neural networks
Tunkiel, Andrzej Tadeusz; Sui, Dan; Wiktorski, Tomasz (Peer reviewed; Journal article, 2020)Machine Learning adoption within drilling is often impaired by the necessity to train the model on data collected from wells analogous in lithology and equipment used to the well where the model is meant to be deployed. ... -
Virtual Field Service Ecosystem (VSE) using AR (Augmented Reality) collaboration with SiemensAG
Gupta, Showmen (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)With the huge advancement of technologies, our viewpoint to see, hear, observe and feel the surroundings around us is changing every single moment. Building a virtual ecosystem is an idea which needs much time and effort. ... -
Visualization of generic utility of sequential patterns
Wiktorski, Tomasz; Królak, Aleksandra; Rosińska, Karolina; Strumillo, Pawel; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2020-05)Most of the literature on utility pattern mining (UPM) assumes that the particular patterns' utility in known in advance. Concurrently, in frequent pattern mining (FPM) it is assumed that all patterns take the same value. ...