Searched for: subject%3A%22Anomaly%255C+detection%22
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Oerlemans, Carlijn (author)
Study objectives: Conventional sleep scoring is based on the scoring criteria of the American Association of Sleep Medicine (AASM) but may not be suited to describe sleep in critically ill children admitted to the Pediatric Intensive Care Unit (PICU). In this study, an anomaly detection model using Gaussian Models trained on sleep stages in data...
master thesis 2024
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Dong, Y. (author), Lu, Xingmin (author), Li, Ruohan (author), Song, Wei (author), van Arem, B. (author), Farah, H. (author)
The burgeoning navigation services using digital maps provide great convenience to drivers. However, there are sometimes anomalies in the lane rendering map images, which might mislead human drivers and result in unsafe driving. To accurately and effectively detect the anomalies, this paper transforms lane rendering image anomaly detection into...
poster 2024
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Ghorbani, R. (author), Reinders, M.J.T. (author), Tax, D.M.J. (author)
Photoplethysmography (PPG) signals, typically acquired from wearable devices, hold significant potential for continuous fitness-health monitoring. In particular, heart conditions that manifest in rare and subtle deviating heart patterns may be interesting. However, robust and reliable anomaly detection within these data remains a challenge...
journal article 2024
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Wen, Minzhen (author), Ibrahim, Mesfin Seid (author), Meda, Abdulmelik Husen (author), Zhang, Kouchi (author), Fan, J. (author)
High-power white light-emitting diodes (LEDs) have demonstrated superior efficiency and reliability compared to traditional white light sources. However, ensuring maximum performance for a prolonged lifetime use presents a significant challenge for manufacturers and end users, especially in safety–critical applications. Thus, identifying...
journal article 2024
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Zhao, Z. (author), Huang, J. (author), Chen, Lydia Y. (author), Roos, S. (author)
Generative Adversarial Networks (GANs) are increasingly adopted by the industry to synthesize realistic images using competing generator and discriminator neural networks. Due to data not being centrally available, Multi-Discriminator (MD)-GANs training frameworks employ multiple discriminators that have direct access to the real data....
conference paper 2024
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Vadachennimalai Selvaraj, Suryaa (author)
The Automatic Identification System (AIS) is used in the maritime domain to improve sea traffic safety by requiring vessels to broadcast real-time information such as identity, speed, location, and course. As it allows global monitoring of almost any larger vessel and has the potential to considerably improve vessel traffic services and...
master thesis 2023
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Timmerman, Gerben (author)
This thesis offers a comprehensive exploration of log-based anomaly detection within the domain of cybersecurity incident response. The research describes a different approach and explores relevant log features for language model training, experimentation with different language models and training methodologies, and the investigation of the...
master thesis 2023
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de Ruijter, Pim (author)
The detection of anomalous behaviour is fundamental to component health analysis techniques. However, detecting anomalies is a difficult and time consuming task if their form, location, and frequency are unknown. This research introduces an innovative unsupervised predictive maintenance pipeline that requires minimal domain knowledge and time to...
master thesis 2023
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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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Hofman, Daan (author)
With the ever-increasing digitalisation of society and the explosion of internet-enabled devices with the Internet of Things (IoT), keeping services and devices secure is becoming more important. Logs play a critical role in sustaining system reliability. Manual analysis of logs has become increasingly difficult, accelerating the development of...
master thesis 2023
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Herrmann, Lars (author)
As the volume of telemetry data generated by satellites and other complex systems continues to grow, there is a pressing need for more efficient and accurate anomaly detection methods. Current techniques often rely on human analysis and preset criteria, presenting several challenges including the necessity for expert interpretation and continual...
master thesis 2023
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Thomas, Wessel (author)
Network Intrusion Detection Systems (NIDSs) defend our computer networks against malicious network attacks. Anomaly-based NIDSs use machine learning classifiers to categorise incoming traffic. Research has shown that classifiers are vulnerable to adversarial examples, perturbed inputs that lead the classifier into misclassifying the input....
master thesis 2023
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Verdoes, Max (author)
Chain belt conveyors have become a popular choice for transporting materials in diverse industries. The primary driving force behind these conveyors is the gearmotor, which is composed of an electric motor and a gear unit. The industrial electric motor market is estimated to be 21 billion USD and consumes up to 70\% of the electricity by the...
master thesis 2023
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Wang, C. (author)
The scale of the power system has been significantly expanded in recent decades. To gain real-time insights into the power system, an increasing number of sensors have been deployed tomonitor grid states, resulting in a rapidly growing number of measurement points. Simultaneously, there has also been a rise in the penetration of renewable energy...
doctoral thesis 2023
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Rajesh, A. (author), Ya, Wei (author), Hermans, M.J.M. (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...
journal article 2023
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Dong, Y. (author), Chen, Kejia (author), Ma, Zhiyuan (author)
Condition-based maintenance is becoming increasingly important in hydraulic systems. However, anomaly detection for these systems remains challenging, especially since that anomalous data is scarce and labeling such data is tedious and even dangerous. Therefore, it is advisable to make use of unsupervised or semi-supervised methods, especially...
conference paper 2023
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Bieber, M.T. (author), Verhagen, W.J.C. (author), Cosson, Fabrice (author), Santos, Bruno F. (author)
Spacecraft systems collect health-related data continuously, which can give an indication of the systems’ health status. While they rarely occur, the repercussions of such system anomalies, faults, or failures can be severe, safety-critical and costly. Therefore, the data are used to anticipate any kind of anomalous behaviour. Typically this is...
journal article 2023
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Bongaerts, Michiel (author), Kulkarni, Purva (author), Zammit, Alan (author), Bonte, Ramon (author), Kluijtmans, Leo A. J. (author), Blom, Henk J. (author), Engelke, Udo F. H. (author), Tax, D.M.J. (author), Ruijter, George J.G. (author), Reinders, M.J.T. (author)
Untargeted metabolomics (UM) is increasingly being deployed as a strategy for screening patients that are suspected of having an inborn error of metabolism (IEM). In this study, we examined the potential of existing outlier detection methods to detect IEM patient profiles. We benchmarked 30 different outlier detection methods when applied to...
journal article 2023
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Presekal, A. (author), Stefanov, Alexandru (author), Subramaniam Rajkumar, Vetrivel (author), Palensky, P. (author)
Electrical power grids are vulnerable to cyber attacks, as seen in Ukraine in 2015 and 2016. However, existing attack detection methods are limited. Most of them are based on power system measurement anomalies that occur when an attack is successfully executed at the later stages of the cyber kill chain. In contrast, the attacks on the Ukrainian...
journal article 2023
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Liu, Minne (author), Ibrahim, Mesfin S. (author), Wen, Minzhen (author), Li, Sheng (author), Wang, An (author), Zhang, Kouchi (author), Fan, J. (author)
Spectral power distribution (SPD) is the radiation power intensity at different wavelengths, containing the most basic photometric and colorimetric performance of the illuminant, which is able to predict the lifetime of LEDs. This paper proposes an SPD model assisted by machine learning algorithms to detect the early failure of white LEDs. The...
conference paper 2023
Searched for: subject%3A%22Anomaly%255C+detection%22
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