Blar i UiS Brage på forfatter "Wiktorski, Tomasz"
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Investigation and study on reinforcement learning for optimizing well path
Chowdhury, Samiul Ehsan (Master thesis, 2021)Designing an optimal path has been considered one of the key challenges for drilling engineers. Even for a group of competent engineers, it takes many months to plan a well. A robust optimized path can influence total cost ... -
Machine Learning Based System Health Check Analyzer For Energy Components
Alex, Anju (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)In any system health check is an important measure, which provides details on how the system is performing and whether there is a need for an intervention manual or automated to correct any anomaly. There are several ... -
Methods for preprocessing time and distance series data from personal monitoring devices
Wiktorski, Tomasz; Bjørkavoll-Bergseth, Magnus; Ørn, Stein (Peer reviewed; Journal article, 2020-06)There is a need to develop more advanced tools to improve guidance on physical exercise to reduce risk of adverse events and improve benefits of exercise. Vast amounts of data are generated continuously by Personal Monitoring ... -
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 ... -
Open shop scheduling in a manufacturing company using machine learning
Strand, Håkon Hapnes (Master thesis, 2016-12-12)Scheduling jobs in a manufacturing company that delivers custom products is challenging. Aarbakke is a company that manufactures advanced assemblies for the oil and gas industry. Its existing resource planning tool frequently ... -
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 ... -
Prediction, interpolation and extrapolation of drilling data with Deep Learning
Tunkiel, Andrzej (Doctoral thesis, 2022-11)Directional drilling is an established technology within the petroleum industry. In this traditionally conservative and risk averse environment application of artificial intelligence encounters difficulties at various ... -
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 ... -
Reference Dataset for Rate of Penetration Benchmarking
Tunkiel, Andrzej Tadeusz; Sui, Dan; Wiktorski, Tomasz (Peer reviewed; Journal article, 2020-10)In recent years, there were multiple papers published related to rate of penetration prediction using machine learning vastly outperforming analytical methods. There are models proposed reportedly achieving R2 values as ... -
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. ...