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Naseri Jahfari, A. (author), Tax, D.M.J. (author), van der Harst, Pim (author), Reinders, M.J.T. (author), van der Bilt, Ivo (author)
Background: Smartwatches enable continuous and noninvasive time series monitoring of cardiovascular biomarkers like heart rate (from photoplethysmograms), step counter, skin temperature, et cetera; as such, they have promise in assisting in early detection and prevention of cardiovascular disease. Although these biomarkers may not be directly...
journal article 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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Garrido, Ángel Luis (author), Pera, M.S. (author), Bobed, Carlos (author)
Recommender Systems support a broad range of domains, each with peculiarities that recommendation algorithms must consider to produce appropriate suggestions. In the paper, we bring attention to a little-studied scenario related to the news domain: recommendations catering to media journalists. Based on the particular needs inherent to a...
journal article 2023
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Nadeem, A. (author), Vos, D.A. (author), Cao, C.S. (author), Pajola, Luca (author), Dieck, S. (author), Baumgartner, R. (author), Verwer, S.E. (author)
Explainable Artificial Intelligence (XAI) aims to improve the transparency of machine learning (ML) pipelines. We systematize the increasingly growing (but fragmented) microcosm of studies that develop and utilize XAI methods for defensive and offensive cybersecurity tasks. We identify 3 cybersecurity stakeholders, i.e., model users, designers,...
conference paper 2023
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Li, Zirui (author), Gong, Cheng (author), Lin, Yunlong (author), Li, G. (author), Wang, Xinwei (author), Lu, Chao (author), Wang, Miao (author), Chen, Shanzhi (author), Gong, Jianwei (author)
Modelling, predicting and analysing driver behaviours are essential to advanced driver assistance systems (ADAS) and the comprehensive understanding of complex driving scenarios. Recently, with the development of deep learning (DL), numerous driver behaviour learning (DBL) methods have been proposed and applied in connected vehicles (CV) and...
review 2023
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Ma, Jinbo (author), Dai, Jiaxin (author), Guo, Xin (author), Fu, Dongmei (author), Ma, Lingwei (author), Keil, Patrick (author), Mol, J.M.C. (author), Zhang, Dawei (author)
Following the construction of a dataset of cross-category corrosion inhibitors at different concentrations based on 1241 data from 184 research papers, a performance prediction model incorporating 2D–3D molecular graph representation and corrosion inhibitor concentration information was established. This model was shown to effectively predict...
journal article 2023
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Bugaje, A.-.A.B. (author), Cremer, Jochen (author), Strbac, Goran (author)
This paper presents a novel, unified approach for generating high-quality datasets for training machine-learned models for real-time security assessment in power systems. Synthetic data generation methods that extrapolate beyond historical data can be inefficient in generating feasible and rare operating conditions (OCs). The proposed...
journal article 2023
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Liu, Zhengxuan (author), Zhang, Xiang (author), Sun, Ying (author), Zhou, Yuekuan (author)
Advanced controls have attracted increasing interests due to the high requirement on smart and energy-efficient (SEE) buildings and decarbonization in the building industry with optimal tradeoff strategies between energy consumption and thermal comfort of built environment. However, a state-of-the-art review is lacking on advanced controls...
journal article 2023
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Yamada, Kenta (author), Fernandes, Bruno Ramon Batista (author), Kalamkar, Atharva (author), Jeon, Jonghyeon (author), Delshad, Mojdeh (author), Farajzadeh, R. (author), Sepehrnoori, Kamy (author)
Depleted gas reservoirs are attractive sites for Carbon Capture and Storage (CCS) due to their huge storage capacities, proven seal integrity, existing infrastructure and subsurface data availability. However, CO<sub>2</sub> injection into depleted formations can potentially lead to hydrate formation near the wellbore due to Joule-Thomson...
journal article 2023
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Tselentis, D. (author), Papadimitriou, E. (author)
Driver behavior analytics is an important concept that plays a significant role in the understanding of road crashes. This paper investigates the optimal number of driver profiles to understand the most important characteristics that differentiate drivers and extract useful insights on the value of using different clustering approaches in...
journal article 2023
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Tavakoli, Ali (author), Hashemi, Javad (author), Najafian, Mahyar (author), Ebrahimi, Amin (author)
Solid-liquid phase transformation of a phase change material in a rectangular enclosure with corrugated fins is studied. Employing a physics-based model, the influence of fin length, thickness, and wave amplitude on the thermal and fluid flow fields is explored. Incorporating fins into thermal energy storage systems enhances the heat transfer...
journal article 2023
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Diez Sanhueza, R.G. (author), Akkerman, I. (author), Peeters, J.W.R. (author)
Turbulent flows past rough surfaces can create substantial energy losses in engineering equipment. During the last decades, developing accurate correlations to predict the thermal and hydrodynamic behavior of rough surfaces has proven to be a difficult challenge. In this work, we investigate the applicability of convolutional neural networks...
journal article 2023
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Bernardini, Giulia (author), van Iersel, L.J.J. (author), Julien, E.A.T. (author), Stougie, Leen (author)
Background: Combining a set of phylogenetic trees into a single phylogenetic network that explains all of them is a fundamental challenge in evolutionary studies. Existing methods are computationally expensive and can either handle only small numbers of phylogenetic trees or are limited to severely restricted classes of networks. Results: In...
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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Bode, Lukas (author), Weinmann, M. (author), Klein, Reinhard (author)
Extracting high-level structural information from 3D point clouds is challenging but essential for tasks like urban planning or autonomous driving requiring an advanced understanding of the scene at hand. Existing approaches are still not able to produce high-quality results consistently while being fast enough to be deployed in scenarios...
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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Hernández, J.I. (author), van Cranenburgh, S. (author), Chorus, C.G. (author), Mouter, N. (author)
We propose three procedures based on association rules (AR) learning and random forests (RF) to support the specification of a portfolio choice model applied in data from complex choice experiment data, specifically a Participatory Value Evaluation (PVE) choice experiment. In a PVE choice experiment, respondents choose a combination of...
journal article 2023
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Dell'Anna, D. (author), Aydemir, Fatma Başak (author), Dalpiaz, Fabiano (author)
Context: Automated classifiers, often based on machine learning (ML), are increasingly used in software engineering (SE) for labelling previously unseen SE data. Researchers have proposed automated classifiers that predict if a code chunk is a clone, if a requirement is functional or non-functional, if the outcome of a test case is non...
journal article 2023
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Bugaje, A.-.A.B. (author), Cremer, Jochen (author), Strbac, Goran (author)
Machine learning (ML) for real-time security assessment requires a diverse training database to be accurate for scenarios beyond historical records. Generating diverse operating conditions is highly relevant for the uncertain future of emerging power systems that are completely different to historical power systems. In response, for the first...
journal article 2023
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Reed, Emily A. (author), Ramos, Guilherme (author), Bogdan, Paul (author), Gonçalves Melo Pequito, S.D. (author)
Finding strongly connected components (SCCs) and the diameter of a directed network play a key role in a variety of machine learning and control theory problems. In this article, we provide for the first time a scalable distributed solution for these two problems by leveraging dynamical consensus-like protocols to find the SCCs. The proposed...
journal article 2023
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