Searched for: subject:"Machine%5C+learning"
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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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Perez-Del-Pulgar, C. J. (author), Smisek, J. (author), Rivas-Blanco, Irene (author), Schiele, A. (author), Munoz, V. 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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Bliek, L. (author)
Beamforming is a signal processing technique used in highly directional antennas. An array of antenna elements transmits the same signal, but with a different time delay for each element. By providing the right time delays for each antenna element, the whole array transmits a high-powered signal in one desired direction. This technique can be...
doctoral thesis 2019
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Kovalenko, V.V. (author), Bogomolov, Egor (author), Bryksin, Timofey (author), Bacchelli, A. (author)
One recent, significant advance in modeling source code for machine learning algorithms has been the introduction of path-based representation - an approach consisting in representing a snippet of code as a collection of paths from its syntax tree. Such representation efficiently captures the structure of code, which, in turn, carries its...
conference paper 2019
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Zhang, Y. (author)
Among all the contributors to fatal accidents, in-flight loss of control (LOC-I) remains one of the largest categories, as indicated by statistics of investigations into past civil aircraft accidents. In flight LOC generally refers to accidents in which the flight crew was unable to maintain control of the aircraft in flight, resulting in an...
doctoral thesis 2019
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Baireuther, P.S. (author), Caio, M. D. (author), Criger, D.B. (author), Beenakker, CWJ (author), O'Brien, T.E. (author)
A quantum computer needs the assistance of a classical algorithm to detect and identify errors that affect encoded quantum information. At this interface of classical and quantum computing the technique of machine learning has appeared as a way to tailor such an algorithm to the specific error processes of an experiment - without the need...
journal article 2019
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Cremer, Jochen L. (author), Konstantelos, Ioannis (author), Tindemans, S.H. (author), Strbac, Goran (author)
Supervised machine learning has been successfully used in the past to infer a system's security boundary by training classifiers (also referred to as security rules) on a large number of simulated operating conditions. Although significant research has been carried out on using classifiers for the detection of critical operating points, using...
journal article 2019
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Sarasua, A (author), Urbano, Julián (author), Gómez, Emilia (author)
Metaphors are commonly used in interface design within Human-Computer Interaction (HCI). Interface metaphors provide users with a way to interact with the computer that resembles a known activity, giving instantaneous knowledge or intuition about how the interaction works. A widely used one in Digital Musical Instruments (DMIs) is the conductor...
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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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), More Authors (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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Dubost, Florian (author), Yilmaz, Pinar (author), Adams, Hieab H (author), Bortsova, Gerda (author), Ikram, Mohammad A. (author), Niessen, W.J. (author), Vernooij, Meike W. (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, Nikolaos G. (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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Baltussen, Elisabeth J.M. (author), Brouwer de Koning, Susan G. (author), Sanders, J. (author), Aalbers, A.G.J. (author), Kok, N. F.M. (author), Beets, Geerard L. (author), Hendriks, B.H.W. (author), Sterenborg, Henricus J.C.M. (author), Kuhlmann, K. F.D. (author), Ruers, Theo J.M. (author)
Background: In colorectal cancer surgery there is a delicate balance between complete removal of the tumor and sparing as much healthy tissue as possible. Especially in rectal cancer, intraoperative tissue recognition could be of great benefit in preventing positive resection margins and sparing as much healthy tissue as possible. To better...
journal article 2019
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Rellermeyer, Jan S. (author), Omranian Khorasani, S. (author), Graur, Dan (author), Parthasarathy, Apourva (author)
Emerging Big Data analytics and machine learning applications require a significant amount of computational power. While there exists a plethora of large-scale data processing frameworks which thrive in handling the various complexities of data-intensive workloads, the ever-increasing demand of applications have made us reconsider the...
conference paper 2019
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de Kok, Roos E. (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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Hirvasniemi, J. (author), Gielis, Willem Paul (author), Arbabi, S. (author), Agricola, R (author), van Spil, W.E. (author), Arbabi, V. (author), Weinans, H.H. (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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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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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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Konstantelos, Ioannis (author), Sun, Mingyang (author), Tindemans, S.H. (author), Issad, Samir (author), Panciatici, Patrick (author), Strbac, Goran (author)
The increasing uncertainty that surrounds electricity system operation renders security assessment a highly challenging task; the range of possible operating states expands, rendering traditional approaches based on heuristic practices and ad hoc analysis obsolete. In turn, machine learning can be used to construct surrogate models...
journal article 2019
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Bouts, Mark J.R.J. (author), Van Der Grond, Jeroen (author), Vernooij, Meike W. (author), Koini, Marisa (author), Schouten, T.M. (author), de Vos, Frank (author), Feis, Rogier A. (author), Lechner, Anita (author), Niessen, W.J. (author), More Authors (author)
Early and accurate mild cognitive impairment (MCI) detection within a heterogeneous, nonclinical population is needed to improve care for persons at risk of developing dementia. Magnetic resonance imaging (MRI)-based classification may aid early diagnosis of MCI, but has only been applied within clinical cohorts. We aimed to determine the...
journal article 2019
Searched for: subject:"Machine%5C+learning"
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