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Liang, M. (author)
Since the introduction of cementitious materials, shrinkage-induced earlyage cracking (EAC) has emerged as a significant issue that negatively influences the function, durability, and aesthetics of concrete structures like dams, tunnels, and underground garages. This thesis aims to develop new experimental and modelling techniques that help...
doctoral thesis 2024
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Ale Ebrahim Dehkordi, Molood (author)
In society, institutions are the foundation that governs human behaviour through rules, norms, and regulations. The actions and interactions of individuals are shaped by these institutions, forming a cyclic system with numerous parameters and factors. Altering any of these factors, triggers the entire system to transition into a new state that...
doctoral thesis 2024
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Ilardi, Davide (author), Kalikatzarakis, Miltiadis (author), Oneto, Luca (author), Collu, Maurizio (author), Coraddu, A. (author)
Due to increasing environmental concerns and global energy demand, the development of Floating Offshore Wind Turbines (FOWTs) is on the rise. FOWTs offer a promising solution to expand wind farm deployment into deeper waters with abundant wind resources. However, their harsh operating conditions and lower maturity level compared to fixed...
journal article 2024
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Narin, O.G. (author), Abdikan, Saygin (author), Gullu, Mevlut (author), Lindenbergh, R.C. (author), Balik Sanli, Fusun (author), Yilmaz, Ibrahim (author)
Open source Global Digital Elevation Models (GDEMs) serve as an important base for studies in geosciences. However, these models contain vertical errors due to various reasons. In this study, data from two Satellite LiDAR altimetry systems, GEDI and ICESat-2, were used to improve the vertical accuracy of GDEMs. Three different machine learning...
journal article 2024
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Kalikadien, A.V. (author), Mirza, Adrian (author), Hossaini, Aydin Najl (author), Sreenithya, Avadakkam (author), Pidko, E.A. (author)
In the past decade, computational tools have become integral to catalyst design. They continue to offer significant support to experimental organic synthesis and catalysis researchers aiming for optimal reaction outcomes. More recently, data-driven approaches utilizing machine learning have garnered considerable attention for their expansive...
journal article 2024
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Sadrtdinova, Renata (author), Perez, Gerald Augusto Corzo (author), Solomatine, D.P. (author)
Kazakhstan is recently experiencing an increase in drought trends. However, low-capacity probabilistic drought forecasts and poor dissemination have led to a drought crisis in 2021 that resulted in the loss of thousands of livestock. To improve drought forecasting accuracy, this study applies Machine Learning and Deep Learning (ML and DL)...
journal article 2024
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Kollert, Andreas (author), Mayr, Andreas (author), Dullinger, Stefan (author), Hülber, Karl (author), Moser, Dietmar (author), Lhermitte, S.L.M. (author), Gascoin, Simon (author), Rutzinger, Martin (author)
Imagery acquired by the Moderate-resolution Imaging Spectroradiometer (MODIS) provides a global archive of dailyNormalized Difference Snow Index (NDSI) at 500 m nominal resolution since the year 2000. While Sentinel-2 (S2) NDSI provides an increased spatial resolution of 20 m since the year 2015, the temporal resolution amounts to only 5 days...
journal article 2024
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Xiao, Y. (author)
Additively manufacturing can bring opportunities and risk factors to the aerospace industry. On one hand, additive manufacturing allows the manufacturing of structures with geometries that are difficult or impossible to fabricatewith conventional machining procedures. This geometry flexibility may lead to components with a greater strength-to...
doctoral thesis 2023
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Köylü, T.C. (author)
Machine learning has gained a lot of recognition recently and is now being used in many important applications. However, this recognition was limited in the hardware security area. Especially, very few approaches depend on this powerful tool to detect attacks during operation. This thesis reduces this gap in the field of fault injection attack...
doctoral thesis 2023
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Mourragui, S.M.C. (author)
Extensive efforts in cancer research over the past decades have markedly improved diagnosis and treatments, leading to better outcomes for cancer patients. Paradoxically, however, these discoveries have begun to shed light on a level of complexity that rules out the emergence of a universal cancer treatment. As any tumor is now known to be...
doctoral thesis 2023
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Thanh, Hung Vo (author), Ebrahimnia Taremsari, Sajad (author), Ranjbar, Benyamin (author), Mashhadimoslem, Hossein (author), Rahimi, E. (author), Rahimi, Mohammad (author), Elkamel, Ali (author)
Porous carbons as solid adsorbent materials possess effective porosity characteristics that are the most important factors for gas storage. The chemical activating routes facilitate hydrogen storage by adsorbing on the high surface area and microporous features of porous carbon-based adsorbents. The present research proposed to predict H<sub...
journal article 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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Lavrinenko, A.K. (author), Chernyshov, I. (author), Pidko, E.A. (author)
Deep eutectic solvents (DESs) represent an environmentally friendly alternative to conventional organic solvents. Their liquid range determines the areas of application, and therefore, the prediction of solid-liquid equilibrium (SLE) diagrams is essential for developing new DESs. Such predictions are not yet possible by using the current...
journal article 2023
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Rajesh, A. (author), Ya, Wei (author), Hermans, M.J.M. (author)
The current research work investigates the possibility of using machine learning models to deduce the relationship between WAAM (wire arc additive manufacturing) sensor responses and defect presence in the printed part. The work specifically focuses on three materials from the nickel alloy family (Inconel 718, Invar 36 and Inconel 625) and uses...
journal article 2023
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Yuan, Y. (author), Wang, Kaiyi (author), Duives, D.C. (author), Hoogendoorn, S.P. (author), Hoogendoorn-Lanser, S. (author), Lindeman, Rick (author)
Data-driven approaches are helpful for quantitative justification and performance evaluation. The Netherlands has made notable strides in establishing a national protocol for bicycle traffic counting and collecting GPS cycling data through initiatives such as the Talking Bikes program. This article addresses the need for a generic framework to...
journal article 2023
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Peng, C. (author), May, Ali (author), Abeel, T.E.P.M.F. (author)
BackgroundEnteric methane from cow burps, which results from microbial fermentation of high-fiber feed in the rumen, is a significant contributor to greenhouse gas emissions. A promising strategy to address this problem is microbiome-based precision feed, which involves identifying key microorganisms for methane production. While machine...
journal article 2023
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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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Haberfehlner, Helga (author), van de Ven, Shankara S. (author), van der Burg, Sven A. (author), Huber, Florian (author), Georgievska, Sonja (author), Aleo, Ignazio (author), Harlaar, J. (author), Bonouvrié, Laura A. (author), van der Krogt, Marjolein M. (author), Buizer, Annemieke I. (author)
Introduction: Video-based clinical rating plays an important role in assessing dystonia and monitoring the effect of treatment in dyskinetic cerebral palsy (CP). However, evaluation by clinicians is time-consuming, and the quality of rating is dependent on experience. The aim of the current study is to provide a proof-of-concept for a machine...
journal article 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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Tepeli, Y.I. (author), Seale, C.F. (author), P. Gonçalves, Joana (author)
Motivation<br/><br/>Anti-cancer therapies based on synthetic lethality (SL) exploit tumour vulnerabilities for treatment with reduced side effects, by targeting a gene that is jointly essential with another whose function is lost. Computational prediction is key to expedite SL screening, yet existing methods are vulnerable to prevalent selection...
journal article 2023
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