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Sun, W. (author), Katsifodimos, A (author), Hai, R. (author)
The rapid growth of large-scale machine learning (ML) models has led numerous commercial companies to utilize ML models for generating predictive results to help business decision-making. As two primary components in traditional predictive pipelines, data processing, and model predictions often operate in separate execution environments,...
conference paper 2023
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Difrancesco, S. (author), van Baardewijk, J.U. (author), Cornelissen, A.S. (author), Varon, Carolina (author), Hendriks, R.C. (author), Bouwer, A.M. (author)
Wearable sensors offer new opportunities for the early detection and identification of toxic chemicals in situations where medical evaluation is not immediately possible. We previously found that continuously recorded physiology in guinea pigs can be used for early detection of exposure to an opioid (fentanyl) or a nerve agent (VX), as well as...
journal article 2023
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Kruse, N.C. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Due to numerous benefits, radar is considered as an important sensor for human activity classification. The problem of classifying continuous sequences of activities of unconstrained duration has been studied in this work. To tackle this challenge, a radar data processing method utilizing point transformer networks has been proposed. The method...
conference paper 2023
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Hadjisotiriou, George (author), Mansour Pour, K. (author), Voskov, D.V. (author)
In this study, we utilize deep neural networks to approximate operators of a nonlinear partial differential equation (PDE), within the Operator-Based Linearization (OBL) simulation framework, and discover the physical space for a physics-based proxy model with reduced degrees of freedom. In our methodology, observations from a high-fidelity...
conference paper 2023
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Nadeem, A. (author), Verwer, S.E. (author), Yang, Shanchieh Jay (author)
The evolving nature of the tactics, techniques, and procedures used by cyber adversaries have made signature and template based methods of modeling adversary behavior almost infeasible. We are moving into an era of data-driven autonomous cyber defense agents that learn contextually meaningful adversary behaviors from observables. In this chapter...
book chapter 2023
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Fioranelli, F. (author), Guendel, Ronny (author), Kruse, N.C. (author), Yarovoy, Alexander (author)
Driven by its contactless sensing capabilities and the lack of optical images being recorded, radar technology has been recently investigated in the context of human healthcare. This includes a broad range of applications, such as human activity classification, fall detection, gait and mobility analysis, and monitoring of vital signs such as...
conference paper 2023
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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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Alcañiz Moya, A. (author), Lindfors, Anders V. (author), Zeman, M. (author), Ziar, H. (author), Isabella, O. (author)
Machine learning is arising as a major solution for the photovoltaic (PV) power prediction. Despite the abundant literature, the effect of climate on yield predictions using machine learning is unknown. This work aims to find climatic trends by predicting the power of 48 PV systems around the world, equally divided into four climates. An...
journal article 2022
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Van Oort, Bart (author), Cruz, Luis (author), Loni, Babak (author), van Deursen, A. (author)
Machine Learning (ML) projects incur novel challenges in their development and productionisation over traditional software applications, though established principles and best practices in ensuring the project's software quality still apply. While using static analysis to catch code smells has been shown to improve software quality attributes...
conference paper 2022
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