Searched for: collection%253Air
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Knijnenburg, Theo A. (author), Klau, Gunnar W (author), Lorio, Francesco (author), Garnett, Mathew J. (author), McDermott, Ultan (author), Shmulevich, I (author), Wessels, L.F.A. (author)
Mining large datasets using machine learning approaches often leads to models that are hard to interpret and not amenable to the generation of hypotheses that can be experimentally tested. We present ‘Logic Optimization for Binary Input to Continuous Output’ (LOBICO), a computational approach that infers small and easily interpretable logic...
journal article 2016
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Ghavamian, F. (author), Tiso, P. (author), Simone, A. (author)
We demonstrate a Model Order Reduction technique for a system of nonlinear equations arising from the Finite Element Method (FEM) discretization of the three-dimensional quasistatic equilibrium equation equipped with a Perzyna viscoplasticity constitutive model. The procedure employs the Proper Orthogonal Decomposition-Galerkin (POD-G) in...
journal article 2017
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Suryanarayana, Gowri (author), Lago, Jesus (author), Geysen, Davy (author), Aleksiejuk, Piotr (author), Johansson, Christian (author)
Recent research has seen several forecasting methods being applied for heat load forecasting of district heating networks. This paper presents two methods that gain significant improvements compared to the previous works. First, an automated way of handling non-linear dependencies in linear models is presented. In this context, the paper...
journal article 2018
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Neerincx, M.A. (author), Koldijk, Saskia (author), Kraaij, Wessel (author)
Employees often report the experience of stress at work. In the SWELL project we investigate how new context aware pervasive systems can support knowledge workers to diminish stress. The focus of this paper is on developing automatic classifiers to infer working conditions and stress related mental states from a multimodal set of sensor data ...
journal article 2018
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Reale, C. (author), Gavin, Kenneth (author), Librić, Lovorka (author), Jurić-Kaćunić, Danijela (author)
Soil classification is a means of grouping soils into categories according to a shared set of properties or characteristics that will exhibit similar engineering behaviour under loading. Correctly classifying site conditions is an important, costly, and time-consuming process which needs to be carried out at every building site prior to the...
journal article 2018
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Liu, S. (author), Oosterlee, C.W. (author), Bohte, Sander M. (author)
This paper proposes a data-driven approach, by means of an Artificial Neural Network (ANN), to value financial options and to calculate implied volatilities with the aim of accelerating the corresponding numerical methods. With ANNs being universal function approximators, this method trains an optimized ANN on a data set generated by a...
journal article 2019
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Paltrinieri, Nicola (author), Comfort, Louise (author), Reniers, G.L.L.M.E. (author)
Risk assessment has a primary role in safety-critical industries. However, it faces a series of overall challenges, partially related to technology advancements and increasing needs. There is currently a call for continuous risk assessment, improvement in learning past lessons and definition of techniques to process relevant data, which are...
journal article 2019
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Dwivedi, Yogesh K. (author), Hughes, Laurie (author), Ismagilova, Elvira (author), Aarts, Gert (author), Coombs, Crispin (author), Crick, Tom (author), Duan, Yanqing (author), Dwivedi, Rohita (author), Janssen, M.F.W.H.A. (author)
As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation...
journal article 2019
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Kim, Jaehun (author), Picek, S. (author), Heuser, Annelie (author), Bhasin, Shivam (author), Hanjalic, A. (author)
Profiled side-channel analysis based on deep learning, and more precisely Convolutional Neural Networks, is a paradigm showing significant potential. The results, although scarce for now, suggest that such techniques are even able to break cryptographic implementations protected with countermeasures. In this paper, we start by proposing a new...
journal article 2019
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de Kok, Roos (author), Mauri, A. (author), Bozzon, A. (author)
Understanding and improving the energy consumption behavior of individuals is considered a powerful approach to improve energy conservation and stimulate energy efficiency. To motivate people to change their energy consumption behavior, we need to have a thorough understanding of which energy-consuming activities they perform and how these...
journal article 2019
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Schmelzer, M. (author), Dwight, R.P. (author), Cinnella, Paola (author)
A novel deterministic symbolic regression method SpaRTA (Sparse Regression of Turbulent Stress Anisotropy) is introduced to infer algebraic stress models for the closure of RANS equations directly from high-fidelity LES or DNS data. The models are written as tensor polynomials and are built from a library of candidate functions. The machine...
journal article 2019
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Dubost, Florian (author), Yilmaz, Pinar (author), Adams, Hieab (author), Bortsova, Gerda (author), Ikram, M. Arfan (author), Niessen, W.J. (author), Vernooij, Meike (author), de Bruijne, Marleen (author)
Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, are common in aging, and are considered a reflection of cerebral small vessel disease. As such, assessing the burden of PVS has promise as a brain imaging marker. Visual and manual scoring of PVS is a tedious and observer-dependent task. Automated methods would...
journal article 2019
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Peternel, L. (author), Fang, Cheng (author), Tsagarakis, Nikos (author), Ajoudani, Arash (author)
In this paper, we propose a method for selective monitoring and management of human muscle fatigue in human-robot co-manipulation scenarios. The proposed approach uses a machine learning technique to learn the complex relationship between individual human muscle forces, arm configuration and arm endpoint force that are provided by a...
journal article 2019
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Hirvasniemi, J. (author), Gielis, W. P. (author), Arbabi, S. (author), Agricola, R. (author), van Spil, W. E. (author), Arbabi, V. (author), Weinans, Harrie (author)
Objective: To assess the ability of radiography-based bone texture variables in proximal femur and acetabulum to predict incident radiographic hip osteoarthritis (rHOA) over a 10 years period. Design: Pelvic radiographs from CHECK at baseline (987 hips) were analyzed for bone texture using fractal signature analysis (FSA) in proximal femur...
journal article 2019
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Bangira, T. (author), Alfieri, S.M. (author), Menenti, M. (author), van Niekerk, Adriaan (author)
Small reservoirs play an important role in mining, industries, and agriculture, but storage levels or stage changes are very dynamic. Accurate and up-to-date maps of surface water storage and distribution are invaluable for informing decisions relating to water security, flood monitoring, and water resources management. Satellite remote...
journal article 2019
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Liu, S. (author), Borovykh, Anastasia (author), Grzelak, L.A. (author), Oosterlee, C.W. (author)
A data-driven approach called CaNN (Calibration Neural Network) is proposed to calibrate financial asset price models using an Artificial Neural Network (ANN). Determining optimal values of the model parameters is formulated as training hidden neurons within a machine learning framework, based on available financial option prices. The...
journal article 2019
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Picek, S. (author), Heuser, Annelie (author), Jovic, Alan (author), Batina, Lejla (author)
Profiled side-channel attacks consist of several steps one needs to take. An important, but sometimes ignored, step is a selection of the points of interest (features) within side-channel measurement traces. A large majority of the related works start the analyses with an assumption that the features are preselected. Contrary to this...
journal article 2019
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Shen, Chunguang (author), Wang, Chenchong (author), Wei, Xiaolu (author), Li, Yong (author), van der Zwaag, S. (author), Xu, W. (author)
With the development of the materials genome philosophy and data mining methodologies, machine learning (ML) has been widely applied for discovering new materials in various systems including high-end steels with improved performance. Although recently, some attempts have been made to incorporate physical features in the ML process, its...
journal article 2019
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Ghavamian, F. (author), Simone, A. (author)
FE<sup>2</sup> multiscale simulations of history-dependent materials are accelerated by means of a recurrent neural network (RNN) surrogate for the history-dependent micro level response. We propose a simple strategy to efficiently collect stress–strain data from the micro model, and we modify the RNN model such that it resembles a nonlinear...
journal article 2019
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Pérez-Del-Pulgar, Carlos J. (author), Smisek, J. (author), Rivas-Blanco, Irene (author), Schiele, A. (author), Muñoz, Victor F. (author)
Haptic guidance is a promising method for assisting an operator in solving robotic remote operation tasks. It can be implemented through different methods, such as virtual fixtures, where a predefined trajectory is used to generate guidance forces, or interactive guidance, where sensor measurements are used to assist the operator in real-time...
journal article 2019
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