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A human-centric machine learning based personalized route choice prediction in navigation systems

Sun, Bingrong (author), Gong, Lin (author), Shim, J. (author), Jang, Kitae (author), Park, B. Brian (author), Wang, Hongning (author), Hu, Jia (author)

Real-world route navigation data indicate that nontrivial portion of drivers do not prefer the system-recommended best routes. Current navigation systems have simplified assumptions about drivers’ route choice preferences and do not adequately accommodate drivers’ heterogeneous route choice preferences, mainly because of: (i) difficulty in...

journal article 2022

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Massive Uncoordinated Multiple Access for Beyond 5G

Mohammadkarimi, M. (author), Dobre, Octavia A. (author), Win, Moe Z. (author)

Existing wireless communication systems have been mainly designed to provide substantial gain in terms of data rates. However, 5G and Beyond will depart from this scheme, with the objective not only to provide services with higher data rates. One of the main goals is to support massive machine-type communications (mMTC) in the Internet-of-Things...

journal article 2022

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Understanding and predicting the occurrence of void street interfaces

De Carvalho Filho, L.M. (author), Sulis, P. (author)

Void street interfaces (VSIs) – building plinths with restricted visual interaction, accessibility, and public use – constitute an urban feature often associated with undermining the public domain, limiting free access and preventing interaction between social groups. Moreover, VSIs have been described as products of inequality designed to...

journal article 2022

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Lead Detection in the Arctic Ocean from Sentinel-3 Satellite Data: A Comprehensive Assessment of Thresholding and Machine Learning Classification Methods

Bij de Vaate, I. (author), Martin, Ericka (author), Slobbe, D.C. (author), Naeije, M.C. (author), Verlaan, M. (author)

In the Arctic Ocean, obtaining water levels from satellite altimetry is hampered by the presence of sea ice. Hence, water level retrieval requires accurate detection of fractures in the sea ice (leads). This paper describes a thorough assessment of various surface type classification methods, including a thresholding method, nine supervised-,...

journal article 2022

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PLIS: A metabolomic response monitor to a lifestyle intervention study in older adults

Bogaards, Fatih A. (author), Gehrmann, Thies (author), Beekman, Marian (author), van den Akker, E.B. (author), van de Rest, Ondine (author), Hangelbroek, Roland W.J. (author), Noordam, Raymond (author), Mooijaart, Simon P. (author), Reinders, M.J.T. (author)

The response to lifestyle intervention studies is often heterogeneous, especially in older adults. Subtle responses that may represent a health gain for individuals are not always detected by classical health variables, stressing the need for novel biomarkers that detect intermediate changes in metabolic, inflammatory, and immunity-related...

journal article 2022

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A Learning-Based Optimization Approach for Autonomous Ridesharing Platforms with Service-Level Contracts and On-Demand Hiring of Idle Vehicles

Alves Beirigo, B. (author), Schulte, F. (author), Negenborn, R.R. (author)

Current mobility services cannot compete on equal terms with self-owned mobility products concerning service quality. Because of supply and demand imbalances, ridesharing users invariably experience delays, price surges, and rejections. Traditional approaches often fail to respond to demand fluctuations adequately because service levels are,...

journal article 2022

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Enabling Co-Innovation for a Successful Digital Transformation in Wind Energy Using a New Digital Ecosystem and a Fault Detection Case Study

Barber, Sarah (author), Lima, Luiz Andre Moyses (author), Sakagami, Yoshiaki (author), Quick, Julian (author), Latiffianti, Effi (author), Liu, Y. (author), Ferrari, Riccardo M.G. (author), Letzgus, Simon (author), Zhang, Xujie (author), Hammer, Florian (author)

In the next decade, further digitalisation of the entire wind energy project lifecycle is expected to be a major driver for reducing project costs and risks. In this paper, a literature review on the challenges related to implementation of digitalisation in the wind energy industry is first carried out, showing that there is a strong need for...

journal article 2022

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Assessment of data consistency through cascades of independently recurrent inference machines for fast and robust accelerated MRI reconstruction

Karkalousos, D. (author), Noteboom, S. (author), Hulst, H. E. (author), Vos, F.M. (author), Caan, M.W.A. (author)

Objective. Machine Learning methods can learn how to reconstruct magnetic resonance images (MRI) and thereby accelerate acquisition, which is of paramount importance to the clinical workflow. Physics-informed networks incorporate the forward model of accelerated MRI reconstruction in the learning process. With increasing network complexity,...

journal article 2022

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Inferring the number of floors for residential buildings

Roy, E.I. (author), Pronk, Maarten (author), Agugiaro, G. (author), Ledoux, H. (author)

Data on the number of floors is required for several applications, for instance, energy demand estimation, population estimation, and flood response plans. Despite this, open data on the number of floors is very rare, even when a 3D city model is available. In practice, it is most often inferred with a geometric method: elevation data is used...

journal article 2022

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Advancing Artificial Neural Network Parameterization for Atmospheric Turbulence Using a Variational Multiscale Model

Janssens, M. (author), Hulshoff, S.J. (author)

Data-driven parameterizations offer considerable potential for improving the fidelity of General Circulation Models. However, ensuring that these remain consistent with the governing equations while still producing stable simulations remains a challenge. In this paper, we propose a combined Variational-Multiscale (VMS) Artificial Neural...

journal article 2022

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A Generalized Transformer-Based Pulse Detection Algorithm

Dematties, Dario (author), Wen, C. (author), Zhang, Shi Li (author)

Pulse-like signals are ubiquitous in the field of single molecule analysis, e.g., electrical or optical pulses caused by analyte translocations in nanopores. The primary challenge in processing pulse-like signals is to capture the pulses in noisy backgrounds, but current methods are subjectively based on a user-defined threshold for pulse...

journal article 2022

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Neural-Network Decoders for Quantum Error Correction Using Surface Codes: A Space Exploration of the Hardware Cost-Performance Tradeoffs

Overwater, R.W.J. (author), Babaie, M. (author), Sebastiano, F. (author)

Quantum error correction (QEC) is required in quantum computers to mitigate the effect of errors on physical qubits. When adopting a QEC scheme based on surface codes, error decoding is the most computationally expensive task in the classical electronic back-end. Decoders employing neural networks (NN) are well-suited for this task but their...

journal article 2022

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A Data-Driven Method for Identifying Drought-Induced Crack-Prone Levees Based on Decision Trees

Chotkan, S.A. (author), van der Meij, Raymond (author), Klerk, Wouter Jan (author), Vardon, P.J. (author), Aguilar Lopez, J.P. (author)

In this paper, we aim to identify factors affecting susceptibility to drought-induced cracking in levees and use them to build a machine learning model that can identify crack-prone levees on a regional scale. By considering the key relationship between the size of cracks and the moisture content, we observed that low moisture contents act as...

journal article 2022

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Graph machine learning for design of high-octane fuels

Rittig, J. (author), Ritzert, Martin (author), Schweidtmann, A.M. (author), Winkler, Stefanie (author), Weber, J.M. (author), Morsch, Philipp (author), Heufer, Karl Alexander (author), Grohe, Martin (author), Mitsos, Alexander (author), Dahmen, Manuel (author)

Fuels with high-knock resistance enable modern spark-ignition engines to achieve high efficiency and thus low CO₂ emissions. Identification of molecules with desired autoignition properties indicated by a high research octane number and a high octane sensitivity is therefore of great practical relevance and can be supported by...

journal article 2022

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A Predictive–Proactive Approach for Slot Management of a Loading Facility With Truck ETA Information

Prakoso, Emanuel Febrianto (author), Maknoon, M.Y. (author), Pel, A.J. (author), Tavasszy, Lorant (author), Vanga, R. (author)

Due to the uncertain and dynamic environment around scheduling systems, timely revisions or reschedules of the master plans are essential for achieving optimal utilization. With the recent development of Industry 4.0 technologies, many researchers perceive the creation of cyber-physical systems as a solution for managing systems under...

journal article 2022

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Learning to Feel Textures: Predicting Perceptual Similarities From Unconstrained Finger-Surface Interactions

Richardson, Benjamin A. (author), Vardar, Y. (author), Wallraven, Christian (author), Kuchenbecker, Katherine J. (author)

Whenever we touch a surface with our fingers, we perceive distinct tactile properties that are based on the underlying dynamics of the interaction. However, little is known about how the brain aggregates the sensory information from these dynamics to form abstract representations of textures. Earlier studies in surface perception all used...

journal article 2022

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Probabilistic Flight Delay Predictions Using Machine Learning and Applications to the Flight-to-Gate Assignment Problem

Zoutendijk, M. (author), Mitici, M.A. (author)

The problem of flight delay prediction is approached most often by predicting a delay class or value. However, the aviation industry can benefit greatly from probabilistic delay predictions on an individual flight basis, as these give insight into the uncertainty of the delay predictions. Therefore, in this study, two probabilistic forecasting...

journal article 2021

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A Study of Learning Search Approximation in Mixed Integer Branch and Bound: Node Selection in SCIP

Yilmaz, Kaan (author), Yorke-Smith, N. (author)

In line with the growing trend of using machine learning to help solve combinatorial optimisation problems, one promising idea is to improve node selection within a mixed integer programming (MIP) branch-and-bound tree by using a learned policy. Previous work using imitation learning indicates the feasibility of acquiring a node selection policy...

journal article 2021

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Aerosol Absorption over Land Derived from the Ultra-Violet Aerosol Index by Deep Learning

Sun, J. (author), Veefkind, j. Pepijn (author), Van Velthoven, Peter (author), Levelt, Pieternel Felicitas (author)

Quantitative measurements of aerosol absorptive properties, e.g., the absorbing aerosol optical depth (AAOD) and the single scattering albedo (SSA), are important to reduce uncertainties of aerosol climate radiative forcing assessments. Currently, global retrievals of AAOD and SSA are mainly provided by the ground-based aerosol robotic...

journal article 2021

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The Stumblemeter: Design and Validation of a System That Detects and Classifies Stumbles during Gait

den Hartog, D.D.G. (author), Harlaar, J. (author), Smit, G. (author)

Stumbling during gait is commonly encountered in patients who suffer from mild to serious walking problems, e.g., after stroke, in osteoarthritis, or amputees using a lower leg prosthesis. Instead of self-reporting, an objective assessment of the number of stumbles in daily life would inform clinicians more accurately and enable the evaluation...

journal article 2021