Searched for: subject:"Machine%5C+Learning"
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Makrodimitris, S. (author)
Billions of people world-wide rely on plant-based food for their daily energy intake. As global warming and the spread of diseases (such as the banana Panama disease) is substantially hindering the cultivation of plants, the need to develop temperature- and/or disease-resistant varieties is getting more and more pressing. The field of plant...
doctoral thesis 2021
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Robbins, S.A. (author)
Machine Learning (ML) is reaching the peak of a hype cycle. If you can think of a personal or grand societal challenge – then ML is being proposed to solve it. For example, ML is purported to be able to assist in the current global pandemic by predicting COVID-19 outbreaks and identifying carriers (see, e.g., Ardabili et al. 2020). ML can make...
doctoral thesis 2021
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Imani, Maryam (author), Hasan, Md Mahmudul (author), Bittencourt, Luiz Fernando (author), McClymont, Kent (author), Kapelan, Z. (author)
Resilience-informed water quality management embraces the growing environmental challenges and provides greater accuracy by unpacking the systems' characteristics in response to failure conditions in order to identify more effective opportunities for intervention. Assessing the resilience of water quality requires complex analysis of...
journal article 2021
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Roest, Laurien I. (author), van Heijst, S.E. (author), Maduro, L.A. (author), Rojo, Juan (author), Conesa Boj, S.C. (author)
Exploiting the information provided by electron energy-loss spectroscopy (EELS) requires reliable access to the low-loss region where the zero-loss peak (ZLP) often overwhelms the contributions associated to inelastic scatterings off the specimen. Here we deploy machine learning techniques developed in particle physics to realise a model...
journal article 2021
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Ye, Qing Chuan (author), Rhuggenaath, Jason. S. (author), Zhang, Yingqian (author), Verwer, S.E. (author), Hilgeman, Michiel Jurgen (author)
Designing auction parameters for online industrial auctions is a complex problem due to highly heterogeneous items. Currently, online auctioneers rely heavily on their experts in auction design. The ability of predicting how well an auction will perform prior to the start comes in handy for auctioneers. If an item is expected to be a low...
journal article 2021
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Jamalinia, E. (author), Sadeghi Tehrani, F. (author), Steele-Dunne, S.C. (author), Vardon, P.J. (author)
Climatic conditions and vegetation cover influence water flux in a dike, and potentially the dike stability. A comprehensive numerical simulation is computationally too expensive to be used for the near real-time analysis of a dike network. Therefore, this study investigates a random forest (RF) regressor to build a data-driven surrogate for a...
journal article 2021
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Tajdari, Mahsa (author), Pawar, Aishwarya (author), Li, Hengyang (author), Tajdari, F. (author), Maqsood, Ayesha (author), Cleary, Emmett (author), Saha, Sourav (author), Zhang, Yongjie Jessica (author), Sarwark, John F. (author), Liu, Wing Kam (author)
Scoliosis, an abnormal curvature of the human spinal column, is characterized by a lateral deviation of the spine, accompanied by axial rotation of the vertebrae. Adolescent Idiopathic Scoliosis (AIS) is the most common type, affecting children between ages 8 to 18 when bone growth is at its maximum rate. We propose a mechanistic machine...
journal article 2021
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van der Waa, J.S. (author), Nieuwburg, Elisabeth (author), Cremers, Anita (author), Neerincx, M.A. (author)
Current developments in Artificial Intelligence (AI) led to a resurgence of Explainable AI (XAI). New methods are being researched to obtain information from AI systems in order to generate explanations for their output. However, there is an overall lack of valid and reliable evaluations of the effects on users' experience of, and behavior in...
journal article 2021
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Derner, Erik (author), Kubalik, Jiri (author), Babuska, R. (author)
Continual model learning for nonlinear dynamic systems, such as autonomous robots, presents several challenges. First, it tends to be computationally expensive as the amount of data collected by the robot quickly grows in time. Second, the model accuracy is impaired when data from repetitive motions prevail in the training set and outweigh...
journal article 2021
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Kulin, Merima (author), Kazaz, T. (author), De Poorter, Eli (author), Moerman, Ingrid (author)
This paper presents a systematic and comprehensive survey that reviews the latest research efforts focused on machine learning (ML) based performance improvement of wireless networks, while considering all layers of the protocol stack: PHY,MAC and network. First, the related work and paper contributions are discussed, followed by providing...
journal article 2021
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van Heijst, S.E. (author), Mukai, Masaki (author), Okunishi, Eiji (author), Hashiguchi, Hiroki (author), Roest, Laurien I. (author), Maduro, L.A. (author), Rojo, Juan (author), Conesa Boj, S.C. (author)
Tailoring the specific stacking sequence (polytypes) of layered materials represents a powerful strategy to identify and design novel physical properties. While nanostructures built upon transition-metal dichalcogenides (TMDs) with either the 2H or 3R crystalline phases have been routinely studied, knowledge of TMD nanomaterials based on...
journal article 2021
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Kudina, O. (author), de Boer, Bas (author)
Rationale: This paper aims to show how the focus on eradicating bias from Machine Learning decision-support systems in medical diagnosis diverts attention from the hermeneutic nature of medical decision-making and the productive role of bias. We want to show how an introduction of Machine Learning systems alters the diagnostic process....
journal article 2021
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Alsayyari, F.S. (author)
Large-scale complex systems require high-fidelity models to capture the dynamics of the system accurately. For example, models of nuclear reactors capture multiphysics interactions (e.g., radiation transport, thermodynamics, heat transfer, and fluid mechanics) occurring at various scales of time (prompt neutrons to burn-up calculations) and...
doctoral thesis 2020
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Heuser, Annelie (author), Picek, S. (author), Guilley, Sylvain (author), Mentens, Nele (author)
Side-channel attacks represent a powerful category of attacks against cryptographic devices. Still, side-channel analysis for lightweight ciphers is much less investigated than for instance for AES. Although intuition may lead to the conclusion that lightweight ciphers are weaker in terms of side-channel resistance, that remains to be...
journal article 2020
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Wang, C. (author), Tindemans, S.H. (author), Pan, K. (author), Palensky, P. (author)
State estimation is of considerable significance for the power system operation and control. However, well-designed false data injection attacks can utilize blind spots in conventional residual-based bad data detection methods to manipulate measurements in a coordinated manner and thus affect the secure operation and economic dispatch of grids....
conference paper 2020
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Virgolin, M. (author), Wang, Ziyuan (author), Alderliesten, T. (author), Bosman, P.A.N. (author)
Purpose: Current phantoms used for the dose reconstruction of long-term childhood cancer survivors lack individualization. We design a method to predict highly individualized abdominal three-dimensional (3-D) phantoms automatically. Approach: We train machine learning (ML) models to map (2-D) patient features to 3-D organ-at-risk (OAR)...
journal article 2020
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Virgolin, M. (author)
Machine learning is impacting modern society at large, thanks to its increasing potential to effciently and effectively model complex and heterogeneous phenomena. While machine learning models can achieve very accurate predictions in many applications, they are not infallible. In some cases, machine learning models can deliver unreasonable...
doctoral thesis 2020
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Muñoz Muñoz, F.A. (author), Mor, A. R. (author)
This paper presents a wavelet analysis technique together with support vector machines (SVM) to discriminate partial discharges (PD) from external disturbances (electromagnetic noise) in a GIS PD measuring system based on magnetic antennas. The technique uses the Cross Wavelet Transform (XWT) to process the PD signals and the external...
journal article 2020
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Kaandorp, Mikael L.A. (author), Dwight, R.P. (author)
A novel machine learning algorithm is presented, serving as a data-driven turbulence modeling tool for Reynolds Averaged Navier-Stokes (RANS) simulations. This machine learning algorithm, called the Tensor Basis Random Forest (TBRF), is used to predict the Reynolds-stress anisotropy tensor, while guaranteeing Galilean invariance by making use...
journal article 2020
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Fan, J. (author), Li, Yutong (author), Fryc, Irena (author), Qian, C. (author), Fan, X. (author), Zhang, Kouchi (author)
The full-spectrum white light-emitting diode (LED) emits light with a broad wavelength range by mixing all lights from multiple LED chips and phosphors. Thus, it has great potentials to be used in healthy lighting, high resolution displays, plant lighting with higher color rendering index close to sunlight and higher color fidelity index. The...
journal article 2020
Searched for: subject:"Machine%5C+Learning"
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