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Helmiriawan, Helmi (author)
Modern refineries typically use a high number of sensors that generate an enormous amount of data about the condition of the plants. This generated data can be used to perform predictive maintenance, an approach to predict impending failures and mitigate downtime in refineries. This research analyzes the scalability of machine learning methods...
master thesis 2018
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Rajesh, Aditya (author)
The current research work investigates the possibility of using machine learning models to deduce the relationship between WAAM (wire arc additive manufacturing) sensor responses and defect presence in the printed part. The work specifically focuses on three materials from the nickel alloy family – Inconel 718, Invar 36 and Inconel 625, and uses...
master thesis 2023
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Ritsma, Folkert (author)
Performance of set based fault detection is highly dependent on the complexity of the set bounding methods used to bound the healthy residual set. Existing methods achieve robust performance with complex set bounding that narrowly define healthy system behavior, yet at the cost of higher computation times. In this thesis a major improvement is...
master thesis 2019
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de Hoog, Dion (author)
In this research, we use different supervised and unsupervised machine learning techniques to detect anomalies in NetFlow data. We aim to create a system for home or small-business use where the user is in control. We use WEKA for the machine learning models and feature selection. The UGR’16 dataset is used to train and test the models. We...
master thesis 2021
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Janowski, Jakub (author)
The resilience of the Air Traffic Management (ATM) system to disturbances is required to maintain high operation performance. Before it can be improved, the resilience of the ATM system must be quantified. The measurement of resilience requires knowledge of a system reference state. This thesis proposes a novel methodology to detect disruptions...
master thesis 2020
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Lan, Yikai (author)
Monitoring the release logs of modern online software is a challenging topic because of the enormous amount of release logs and the complicated release process. The goal of this thesis is to develop a pipeline that can monitor the release logs and find anomalous logs, automating this step with anomaly detection and reducing the required manual...
master thesis 2018
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van Hal, Sven (author)
The cyber arms race has red and blue teams continuously at their toes to keep ahead. Increasingly capable cyber actors breach secure networks at a worrying scale. While network monitoring and analysis should identify blatant data exfiltration attempts, covert channels bypass these measures and facilitate surreptitious information extraction. The...
master thesis 2021
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