107 research outputs found
Marten Jansen: Kort, doch Echt-Verhaal van Commandeur Marten Jansen, Weegens het Verongelukken van zyn Schip ... Waar by nog Copia, van een Brief van Comm. Hidde Dirks Kat ... geschreeven uit Straat-Davids (1778, Leeuwarden)
No full textKort, doch Echt-Verhaal van Commandeur Marten Jansen, Weegens het Verongelukken van zyn Schip, genaamd het Witte Paard, en nog Negen andere Scheepen, dewelke alle Verongelukt zyn, in Groenland, door de bezetting van ’t West Ys, ten Jaare 1777. Men treft in dit Verhaal aan, de wonderlyke behouding van verscheidene Menschen op een Ysschots, waar meede zy eenige Mylen door de Ysbergen zyn heen gedreeven: En andere zeldzaame Ontmoetingen hun al verder voorgekoomen. Waar by nog Copia, van een Brief van Comm. Hidde Dirks Kat, aan zyn Huisvrouw, geschreeven uit Straat-Davids, behelzende meede haare Ongelukken en Rampen op Reis geleden. Te Leeuwarden, By G. Tresling, Boekverkoper in de Peperstraat, 1778
Marten Jansen: Kort, doch Echt-Verhaal van Commandeur Marten Jansen, Weegens het Verongelukken van zyn Schip ... Waar by nog Copia, van een Brief van Comm. Hidde Dirks Kat ... geschreeven uit Straat-Davids (1778, Leeuwarden)
No full textKort, doch Echt-Verhaal van Commandeur Marten Jansen, Weegens het Verongelukken van zyn Schip, genaamd het Witte Paard, en nog Negen andere Scheepen, dewelke alle Verongelukt zyn, in Groenland, door de bezetting van ’t West Ys, ten Jaare 1777. Men treft in dit Verhaal aan, de wonderlyke behouding van verscheidene Menschen op een Ysschots, waar meede zy eenige Mylen door de Ysbergen zyn heen gedreeven: En andere zeldzaame Ontmoetingen hun al verder voorgekoomen. Waar by nog Copia, van een Brief van Comm. Hidde Dirks Kat, aan zyn Huisvrouw, geschreeven uit Straat-Davids, behelzende meede haare Ongelukken en Rampen op Reis geleden. Te Leeuwarden, By G. Tresling, Boekverkoper in de Peperstraat, 1778
ASO Author Reflection: Lateral Pelvic Lymph Nodes in Rectal Cancer—Not All Are Created Equal
No full textHidde M. Kroon, Miranda Kusters, and Tarik Sammou
ASO Author Reflection: Isolated Limb Infusion for Locally Advanced Melanoma in the Extremely Old Patient is Safe and Effective
No full textASO Author reflectionsAbstract unavailableJüri Teras, Hidde M. Kroon and Jonathan S. Zage
ASO Author Reflections: Return to Isolated Limb Infusion for In-Transit Melanoma
No full textASO Author ReflectionsMichael J. Carr, Hidde M. Kroon, and Jonathan S. Zage
Designing compression garments with integrated sensors for enhanced monitoring & treatment
No full textCardiovascular disease is one of the leading causes of death, representing 32% of all global deaths. The mainstay treatments are medical compression stockings (MCS) and physical activity. Although MCS has been shown to positively affect treatment and support disorder control (e.g. leg swelling), research shows incredibly low therapy compliance.Throughout history, the involvement of digital technologies has greatly enhanced healthcare.Nonetheless, developments are not embraced by the medical compression stockings industry yet. For instance, since the invention of medical compression stockings (with a graduated compression) in 1960, the design of medical compression stockings (MCS) has hardly changed.This thesis explores the integration of sensors into medical compression stockings and aims to innovate current compression stockings by including wearable technology. The feasibility and viability of smart stockings are examined, and barriers are defined through a combination of interviews, literature and user observations. Findings are translated into design requirements.Throughout the research, multiple problems have been identified, ranging from user dissatisfaction to product shortcomings.For instance, MCS only have an expected lifespan of half a year. Yet, MCS are yearly reimbursed by health insurance companies. Also, wearing, product care, and health complications can even shorten the lifespan of MCS. For the successful treatment of disorders, it is essential that MCS exert the correct amount of compression.The presented smart stockings with the app address these shortcomings. The smart stocking is able to monitor the exerted compression of MCS. By constantly validating the product, users gain ownership over the quality of their compression therapy.Aside from product validation, compression monitoring is translated into the level of fitness of the user. Increased compression (outside of the walking range) indicates an expanding circumference of the ankle. Together with a vascular surgeon, guidelines are discussed. The combination of the smart stocking and the app has the potential to give medical recommendations to users.With the app, users can be rewarded for their therapy adherence and goals tailored to the specific user and their physical capabilities. Lastly, not every healthcare complication is immediately measurable through compression change. Therefore, the app can ask additional questions based on visible signs, this way it also coaches users to monitor their health.Integrated Product Design | Medisig
ASO Author Reflections: International Experience of Isolated Limb Infusion for Melanoma Shows Durable Response
No full textAbstract unavailableJohn T. Miura, Hidde M. Kroon, and Jonathan S. Zage
Incorporating Inductive Bias into Deep Learning: A Perspective from Automated Visual Inspection in Aircraft Maintenance
No full textThe near-term artificial intelligence, commonly referred as ‘weak AI’ in the last couple years was achieved thanks to the advances in machine learning (ML), particularly deep learning, which has currently the best in-class performance outperforming other machine learning algorithms. In the deep learning framework, many natural tasks such as object, image, and speech recognition that were impossible to be performed by classical ML algorithms in the previous decades can now be be done by typical home personal computer. Deep learning requires large amount of data that has to be rapidly collected (also known as ‘big data’) in order to create robust model parameters that are able to predict future occurrences of certain event. In some domains, a large dataset such as CIFAR-10, MNIST, or Kaggle exist already. However, in many other domains such as aircraft visual inspection, such a large dataset is not easily available and this clearly restricts deep learning to perform well to recognize material damage in aircraft structures. As many computer science researchers believe, we also think that in order to achieve a performance similar to human-level intelligence, AI could and should not start from scratch. Introducing an inductive bias into deep learning might be one solution to achieve that humanlevel intelligence. In this paper, we give an example how to incorporate aerospace domain knowledge into the development of deep learning algorithms. We performed a relatively simple procedure: we conducted fatigue testing of an aluminum plate that is typically used in aircraft fuselage and build a deep convolutional neural network that classifies crack length according to crack propagation curve obtained from fatigue test. The results of this network are then compared to the results of the same network that was not injected by domain knowledgeGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Structural Integrity & CompositesAerospace Structures & Material
Implementing continual learning in autoencoders for Network Intrusion Detection Systems in a practical use case
No full textTo detect intrusions in and therefore protect a computer network, network intrusion detection
systems (NIDS) are broadly used software solutions. Machine learning has shown potential
to be used in these systems. However, implementing such a solution has drawbacks. Primar ily, anomaly-based NIDS can suffer from catastrophic forgetting and have difficulties adapting
to changing environments. As a solution, academics have proposed the concept of continual
learning. In this thesis, possibilities are explored to implement continual learning in NIDS. In
particular, experience replay will be used in an unsupervised autoencoder NIDS.
It first validates the approach on academic datasets, CICIDS-2017 and Kyoto2006, and
then validates the findings on data collected from Northwave Cyber Security. For CICIDS 2017 and real data, no improvement in AUC has been observed. On Kyoto2006, experience
replay improved the AUC for unseen data from 0.6024 to 0.6806, which is an improvement of
7.84%. While this shows potential, more work needs to be done to conclusively evaluate the
performance. This work serves as exploratory study to an implementation of continual learning
in the context of anomaly-based unsupervised NIDS
Instrument Classi cation for Cochlear Implant Filtering using Convolutional Neural Networks
No full textIn this thesis, Convolutional Neural Networks are used to classify instru-
ments in audio les containing musical instruments. In particular, music
enjoyment for Cochlear Implant users is central in this thesis. Therefore,
there are di erent frequency lters applied in the preprocessing, to further
explore the optimal preprocessing when frequency space is limited. The
results show that, in line with previous research, there is a certain range
that is particularly important in instrument recognition. However, in this
research this range di ers, possibly because this research is focused on music
whereas the original research is based on speech. The classi cation when
ltered on this range outperforms the classi cation when presented with the
full spectrum
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