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Dobiczek, Karol (author)
Employing counterfactual explanations in a recourse process gives a positive outcome to an individual, but it also shifts their corresponding data point. For systems where models are updated frequently, a change might be seen when recourse is applied, and after multiple rounds, severe shifts in both model and domain may occur. Algorithmic...
bachelor thesis 2022
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Nguyen, Dean (author)
Learning curves have been used extensively to analyse learners' behaviour and practical tasks such as model selection, speeding up training and tuning models. Nonetheless, we still have a relatively limited understanding of the behaviour of learning curves themselves, in particular, whether there exists a parametric function that can best model...
bachelor thesis 2022
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Kargul, Radek (author)
Spending time in front of screens has become an inescapable activity, which might be interrupted by unrelated external causes. While automatic approaches to identify mind-wandering (MW) have already been investigated, past research was done with self-reports or physiological data. This work explores automated detection utilizing solely facial...
bachelor thesis 2022
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Lek, Gert (author)
The application of machine learning in daily life requires interpretability and robustness. In this paper we try to make the process of building robust and interpretable decision trees more accessible. We do this by making the fitting of these models cheaper and simpler. We build on previous research and see if changing input data or the fitting...
bachelor thesis 2022
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van Heteren, Mauries (author)
The underwater acoustic environment is amongst the most challenging mediums for wireless communications. The three distinct challenges of underwater acoustic communication are the low and nonuniform propagation speed, frequency-dependent attenuation and time-varying multipath propagation.<br/>To cope with these challenges, physical layer...
master thesis 2022
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Ziengs, Bart (author)
Interpretability of ML models and image recognition models specifaclly, is a increasing problem. In this thesis, the design and implementation of Brickroutine: a system that used a trained model, is presented. Using human annotations, semantic interpretations are given to image classification problems. By giving an iterative approach in terms of...
master thesis 2022
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van Zijl, Job (author)
Deep Reinforcement Learning (DRL) shows great potential for flight control, due to its adaptability, fault-tolerance, and as it does not require an accurate system model. However, these techniques, like many machine learning applications, are considered black-box as their inner workings are hidden. This paper aims to break open the black box of...
master thesis 2022
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Treurniet, Wiljo (author)
To achieve the goals on greenhouse gas emissions, the energy supply and demand is in transition. Distribution power grids therefore are increasingly reaching their capacity limits due to electrification and the vast increase of distributed energy resource (DER) connection requests with large peak power output. Increasing physical grid capacity...
master thesis 2022
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Kim, J. (author), Jonoski, Andreja (author), Solomatine, D.P. (author)
Cyanobacterial blooms appear by complex causes such as water quality, climate, and hydrological factors. This study aims to present the machine learning models to predict occurrences of these complicated cyanobacterial blooms efficiently and effectively. The dataset was classified into groups consisting of two, three, or four classes based on...
journal article 2022
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Hajee, Bram (author), Wisse, Kees (author), Mohajerin Esfahani, P. (author)
Multi-sensor networks are becoming more and more popular in order to assess the post-occupancy performance of smart buildings, since they enable continuous monitoring with a high spatial resolution of the occupancy, thermal comfort and indoor air quality. An urgent, but poorly attended topic in this field is the automated detection of sensor...
conference paper 2022
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Nicoletti, L.A. (author), Sirenko, M. (author), Verma, T. (author)
Disparity in spatial accessibility is strongly associated with growing inequalities among urban communities. Since improving levels of accessibility for certain communities can provide them with upward social mobility and address social exclusion and inequalities in cities, it is important to understand the nature and distribution of spatial...
journal article 2022
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de Bruijn, Douwe S. (author), ten Eikelder, Henricus R.A. (author), Papadimitriou, V. (author), Olthuis, Wouter (author), van den Berg, Albert (author)
The assessment of particle and cell size in electrical microfluidic flow cytometers has become common practice. Nevertheless, in flow cytometers with coplanar electrodes accurate determination of particle size is difficult, owing to the inhomogeneous electric field. Pre-defined signal templates and compensation methods have been introduced to...
journal article 2022
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de Graaf, W.M. (author), van Riet, T.C.T. (author), de Lange, J. (author), Kober, J. (author)
Surprisingly little is known about tooth removal procedures. This might be due to the difficulty of gaining reliable data on these procedures. To improve our understanding of these procedures, machine learning techniques were used to design a multiclass classification model of tooth removal based on force, torque, and movement data recorded...
journal article 2022
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Rozsas, Arpad (author), Slobbe, Arthur (author), Huizinga, Wyke (author), Kruithof, Maarten (author), Ajithkumar Pillai, Krishna (author), Kleijn, Kelvin (author), Giardina, Giorgia (author)
This paper proposes an automated approach to predict crack pattern similarities that correlate well with assessment by structural engineers. We use Siamese convolutional neural networks (SCNN) that take two crack pattern images as inputs and output scalar similarity measures. We focus on 2D masonry facades with and without openings. The image...
journal article 2022
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Den Hartog, Dylan (author), van der Krogt, Marjolein M. (author), van der Burg, Sven (author), Aleo, Ignazio (author), Gijsbers, Johannes (author), Bonouvrié, Laura A. (author), Harlaar, J. (author), Buizer, Annemieke I. (author), Haberfehlner, Helga (author)
Accurate and reliable measurement of the severity of dystonia is essential for the indication, evaluation, monitoring and fine‐tuning of treatments. Assessment of dystonia in children and adolescents with dyskinetic cerebral palsy (CP) is now commonly performed by visual evaluation either directly in the doctor’s office or from video...
journal article 2022
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Garzón Díaz, J.A. (author), Kapelan, Z. (author), Langeveld, J.G. (author), Taormina, R. (author)
Surrogate models replace computationally expensive simulations of physically-based models to obtain accurate results at a fraction of the time. These surrogate models, also known as metamodels, have been employed for analysis, control, and optimization of water distribution and urban drainage systems. With the advent of machine learning (ML),...
review 2022
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Di Domenico, Giuseppe (author), Weisman, Dror (author), Panichella, A. (author), Roitman, Dolev (author), Arie, Ady (author)
Spatial modes of light can be used as carriers of information in classical optical communication or as an alphabet in quantum optical communication. In order to exploit the spatial domain, it is required to (de)multiplex different modes from a shared input channel into different output ports. Mode sorters have been employed in free-space and...
journal article 2022
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Zorello, Ligia Maria Moreira (author), Bliek, L. (author), Troia, Sebastian (author), Guns, Tias (author), Verwer, S.E. (author), Maier, Guido (author)
The 5G Radio Access Network (RAN) virtualization aims to improve network quality and lower the operator's costs. One of its main features is the functional split, i.e., dividing the instantiation of RAN baseband functions into different units over metro-network nodes. However, its optimal placement is non-trivial: it depends on the...
journal article 2022
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Mulder, S.T. (author), Omidvari, Amir-Houshang (author), Rueten-Budde, A.J. (author), Hai, R. (author), Akgün, O.C. (author), Tax, D.M.J. (author), Reinders, M.J.T. (author), Reinders, Marcel (author), Visch, V.T. (author)
A digital twin (DT), originally defined as a virtual representation of a physical asset, system, or process, is a new concept in health care. A DT in health care is not a single technology but a domain-adapted multimodal modeling approach incorporating the acquisition, management, analysis, prediction, and interpretation of data, aiming to...
journal article 2022
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Razavi, Saman (author), Hannah, David M. (author), Elshorbagy, Amin (author), Kumar, Sujay (author), Marshall, Lucy (author), Solomatine, D.P. (author), Dezfuli, Amin (author), Sadegh, Mojtaba (author), Famiglietti, James (author)
Machine learning (ML) applications in Earth and environmental sciences (EES) have gained incredible momentum in recent years. However, these ML applications have largely evolved in ‘isolation’ from the mechanistic, process-based modelling (PBM) paradigms, which have historically been the cornerstone of scientific discovery and policy support....
journal article 2022
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