Collection: research
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Sun, Yubo (author), Cheng, H. (author), Zhang, Shizhe (author), Mohan, Manu K. (author), Ye, G. (author), De Schutter, Geert (author)
Alkali-activated concrete (AAC) is regarded as a promising alternative construction material to reduce the CO<sub>2</sub> emission induced by Portland cement (PC) concrete. Due to the diversity in raw materials and complexity of reaction mechanisms, a commonly applied design code is still absent to date. This study attempts to directly...
journal article 2023
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Pandey, Pankaj (author), Rodriguez-Larios, Julio (author), Miyapuram, Krishna Prasad (author), Lomas, J.D. (author)
Electroencephalography (EEG) enables online monitoring brain activity, which can be used for neurofeedback. One of the growing applications of EEG neurofeedback is to facilitate meditation practice. Specifically, EEG neurofeedback can be used to alert participants whenever they get distracted during meditation practice based on changes in their...
conference paper 2023
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Ghasemi, Mostafa (author), Silani, Mohammad (author), Yaghoubi Nasrabadi, V. (author), Concli, Franco (author)
To design a more efficient energy absorber, it is critical to evaluate how changing the design parameters affects its performance, and also determine each one’s order of significance. In this paper, using a new approach, the behavior and response of straight, double-tapered, and triple-tapered thin-walled tubes with rectangular cross sections...
conference paper 2023
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Smeele, Nicholas V.R. (author), Chorus, C.G. (author), Schermer, Maartje H.N. (author), de Bekker-Grob, Esther W. (author)
Background: Discrete choice models (DCMs) for moral choice analysis will likely lead to erroneous model outcomes and misguided policy recommendations, as only some characteristics of moral decision-making are considered. Machine learning (ML) is recently gaining interest in the field of discrete choice modelling. This paper explores the...
review 2023
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Freites, Alfredo (author), Corbett, P. W.M. (author), Rongier, G. (author), Geiger, S. (author)
Understanding the impact of fractures on fluid flow is fundamental for developing geoenergy reservoirs. Pressure transient analysis could play a key role for fracture characterization purposes if better links can be established between the pressure derivative responses (p′) and the fracture properties. However, pressure transient analysis is...
journal article 2023
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Al-Sabaeei, Abdulnaser M. (author), Alhussian, Hitham (author), Abdulkadir, Said Jadid (author), Giustozzi, Filippo (author), Napiah, Madzlan (author), Jagadeesh, A. (author), Sutanto, Muslich (author), Memon, Abdul Muhaimin (author)
The optimization of energy consumption during asphalt mixture production and compaction is a challenge in producing durable, sustainable, and environmentally friendly asphalt products. This study investigated the effects of crude palm oil (CPO) and/or tire pyrolysis oil (TPO) on shear viscosity and mixing and compaction temperatures of...
journal article 2023
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Anikiev, Denis (author), Birnie, Claire (author), Waheed, Umair bin (author), Alkhalifah, Tariq (author), Gu, Chen (author), Verschuur, D.J. (author), Eisner, Leo (author)
The confluence of our ability to handle big data, significant increases in instrumentation density and quality, and rapid advances in machine learning (ML) algorithms have placed Earth Sciences at the threshold of dramatic progress. ML techniques have been attracting increased attention within the seismic community, and, in particular, in...
review 2023
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Grabe, Cornelia (author), Jäckel, Florian (author), Khurana, Parv (author), Dwight, R.P. (author)
Purpose: This paper aims to improve Reynolds-averaged Navier Stokes (RANS) turbulence models using a data-driven approach based on machine learning (ML). A special focus is put on determining the optimal input features used for the ML model. Design/methodology/approach: The field inversion and machine learning (FIML) approach is applied to...
journal article 2023
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Wahdany, D. (author), Schmitt, Carlo (author), Cremer, Jochen (author)
Weather forecast models are essential for sustainable energy systems. However, forecast accuracy may not be the best metric for developing forecast models. A more or less conservative forecast may be preferred over pure accuracy. For example, forecasting accurately in times of energy-deprived situations may be more important than in times of...
journal article 2023
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Varouchakis, Emmanouil A. (author), Solomatine, D.P. (author), Corzo Perez, Gerald A. (author), Jomaa, Seifeddine (author), Karatzas, George P. (author)
Successful modelling of the groundwater level variations in hydrogeological systems in complex formations considerably depends on spatial and temporal data availability and knowledge of the boundary conditions. Geostatistics plays an important role in model-related data analysis and preparation, but has specific limitations when the aquifer...
journal article 2023
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Li, Z. (author), Kant, Henk (author), Hai, R. (author), Katsifodimos, A (author), Brambilla, Marco (author), Bozzon, A. (author)
Machine learning (ML) practitioners and organizations are building model repositories of pre-trained models, referred to as model zoos. These model zoos contain metadata describing the properties of the ML models and datasets. The metadata serves crucial roles for reporting, auditing, ensuring reproducibility, and enhancing interpretability....
journal article 2023
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Koohmishi, Mehdi (author), Guo, Y. (author)
The occurrence of ballast contamination or fouling frequently results in a sudden decline in the capacity of railway ballasted tracks. Considering the various sources of ballast fouling, clay is the most severe one for causing a drastic reduction in the drainage capacity of the ballast layer. In the current study, we utilized a large-scale...
journal article 2023
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van Leer, Martijn D. (author), Zaadnoordijk, Willem (author), Zech, Alraune (author), Buma, Jelle (author), Harting, Ronald (author), Bierkens, Marc F.P. (author), Griffioen, Jasper (author)
Aquitards are common hydrogeological features and their hydraulic conductivity is an important property for various groundwater management issues. Predicting their hydraulic conductivity proves challenging, given its dependence on numerous variables. In this study, the dominant factors for predicting aquitard hydraulic conductivity are...
journal article 2023
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Wilschut, Thomas (author), Sense, Florian (author), Scharenborg, O.E. (author), van Rijn, Hedderik (author)
Cognitive models of memory retrieval aim to describe human learning and forgetting over time. Such models have been successfully applied in digital systems that aid in memorizing information by adapting to the needs of individual learners. The memory models used in these systems typically measure the accuracy and latency of typed retrieval...
conference paper 2023
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de Roda Husman, S. (author), Lhermitte, S.L.M. (author), Bolibar, J. (author), Izeboud, M. (author), Hu, Zhongyang (author), Shukla, S. (author), van der Meer, Marijn (author), Long, David (author), Wouters, B. (author)
While the influence of surface melt on Antarctic ice shelf stability can be large, the duration and affected area of melt events are often small. Therefore, melt events are difficult to capture with remote sensing, as satellite sensors always face the trade-off between spatial and temporal resolution. To overcome this limitation, we developed...
journal article 2023
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de Croon, G.C.H.E. (author)
journal article 2023
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Buijsman, S.N.R. (author)
Machine learning is used more and more in scientific contexts, from the recent breakthroughs with AlphaFold2 in protein fold prediction to the use of ML in parametrization for large climate/astronomy models. Yet it is unclear whether we can obtain scientific explanations from such models. I argue that when machine learning is used to conduct...
journal article 2023
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Ferreira de Brito, B.F. (author)
Autonomous robots will profoundly impact our society, making our roads safer, reducing labor costs and carbon dioxide (CO2) emissions, and improving our life quality. However, to make that happen, robots need to navigate among humans, which is extremely difficult. Firstly, humans do not explicitly communicate their intentions and use intuition...
doctoral thesis 2022
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Gudi, A.A. (author)
Machines that interact with humans can do so better if they can also visually understand us, but they have limited resources to do so. The main topic of this dissertation is contrasting the use of resources by machine vision systems against the accuracy obtained by them. This thesis focuses on reducing the need for data, memory, and computation...
doctoral thesis 2022
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Chandrashekar, A. (author)
Most physical phenomena be it mechanical, chemical or biological are inherently nonlinear in nature. In fact, it is the linear phenomenon that is the exception rather than the rule. By harnessing these nonlinearities one can obtain far greater information about the underlying physics and develop more sensitive and efficient devices. This is...
doctoral thesis 2022
Collection: research
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