Searched for: subject%3A%22Data%255C+models%22
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Siebinga, O. (author), Zgonnikov, A. (author), Abbink, D.A. (author)
Traffic interactions between merging and highway vehicles are a major topic of research, yielding many empirical studies and models of driver behaviour. Most of these studies on merging use naturalistic data. Although this provides insight into human gap acceptance and traffic flow effects, it obscures the operational inputs of interacting...
journal article 2024
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Bachert, Carolin (author), León Sánchez, C.A. (author), Kutzner, Tatjana (author), Agugiaro, G. (author)
With the increasing adoption of semantic 3D city models, the relevance of applications in the field of Urban Building Energy Modelling (UBEM) has rapidly grown, as the building sector accounts for a large part of the total energy consumption. UBEM allows us to better understand the energy performance of the building stock and can contribute to...
journal article 2024
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Inamdar, A.S. (author), Hauck, Torsten (author), van Soestbergen, Michiel (author), van Driel, W.D. (author), Zhang, Kouchi (author)
Model order reduction techniques are developed and utilized to make numerical simulations more efficient. The use of Reduce Order Models (ROM) also enables data exchange with external parties without disclosing the sensitive information present in a Full-Order Model (FOM). It is crucial to optimize for both the efficiency and accuracy of a ROM...
conference paper 2024
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Diware, S.S. (author), Chilakala, Koteswararao (author), Joshi, Rajiv V. (author), Hamdioui, S. (author), Bishnoi, R.K. (author)
Diabetic retinopathy (DR) is a leading cause of permanent vision loss worldwide. It refers to irreversible retinal damage caused due to elevated glucose levels and blood pressure. Regular screening for DR can facilitate its early detection and timely treatment. Neural network-based DR classifiers can be leveraged to achieve such screening in...
journal article 2024
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Murti, Fahri Wisnu (author), Ali, Samad (author), Iosifidis, G. (author), Latva-aho, Matti (author)
Virtualized Radio Access Networks (vRANs) are fully configurable and can be implemented at a low cost over commodity platforms to enable network management flexibility. In this paper, a novel vRAN reconfiguration problem is formulated to jointly reconfigure the functional splits of the base stations (BSs), locations of the virtualized central...
journal article 2024
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Lehner, Hubert (author), Kordasch, Sara Lena (author), Glatz, Charlotte (author), Agugiaro, G. (author)
This paper presents a CityGML-based data model developed for the semantic 3D city model of Vienna, Austria. The data model consists in a profile of the CityGML 2.0 standard and has been extended by means of an Application Domain Extension (ADE) developed by the Department for Surveying and Mapping of the City of Vienna in order to comply with...
conference paper 2024
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Gholinejad, Saeid (author), Amiri Simkooei, A. (author)
Hyperspectral unmixing (HU), an essential procedure for various environmental applications, has garnered significant attention within remote sensing communities. Among different groups of HU methods, nonnegative matrix factorization (NMF)-based ones have gained widespread popularity due to their high capability of simultaneously extracting...
journal article 2024
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Versteeg, Rogier (author), Pool, D.M. (author), Mulder, Max (author)
This article discusses a long short-term memory (LSTM) recurrent neural network that uses raw time-domain data obtained in compensatory tracking tasks as input features for classifying (the adaptation of) human manual control with single- and double-integrator controlled element dynamics. Data from two different experiments were used to train...
journal article 2024
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Karnani, Simran (author)
In recent years, there has been a growing interest among researchers in the explainability, fairness, and robustness of Computer Vision models. While studies have explored the usability of these models for end users, limited research has delved into the challenges and requirements faced by researchers investigating these requirements. This study...
master thesis 2023
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Kadiev, Adam (author)
The goal of this research is to model and understand the effects of tourism demand on air quality by performing data integration on multi-source data. This research is aimed at researchers and practitioners aiming to perform multidisciplinary research in the fields of data science and geoscience, presenting the methods and challenges that arise...
master thesis 2023
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Wei, Xiaoguang (author), Liu, Y. (author), Shi, Jian (author), Gao, Shibin (author), Li, Xingpeng (author), Han, Zhu (author)
This article offers a novel perspective on identifying the critical branches under load redistribution (LR) attacks. Compared to the existing literature that is largely disruption-driven and based on dc state estimation, we propose to address the threat from LR attacks on a more fundamental level by modeling and analyzing the circulation of...
journal article 2023
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Ruan, Tiancheng (author), Wang, Hao (author), Jiang, Rui (author), Li, Xiaopeng (author), Xie, N. (author), Xie, Xinjian (author), Hao, Ruru (author), Dong, Changyin (author)
Urged by a close future perspective of a traffic flow made of a mix of human-driven vehicles and automated vehicles (AVs), research has recently focused on studying the traffic flow characteristics of Adaptive Cruise Controls (ACCs), the most typical AV. However, in most works, the ACC system is studied under a simplifying and unrealistic...
journal article 2023
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Sabbaqi, M. (author), Isufi, E. (author)
Devising and analysing learning models for spatiotemporal network data is of importance for tasks including forecasting, anomaly detection, and multi-agent coordination, among others. Graph Convolutional Neural Networks (GCNNs) are an established approach to learn from time-invariant network data. The graph convolution operation offers a...
journal article 2023
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Nikaein, T. (author), López-Dekker, Paco (author), Steele-Dunne, S.C. (author), Kumar, V. (author), Huber, M. (author)
In this article, our aim is to estimate synthetic aperture radar (SAR) observables, such as backscatter in VV and VH polarizations, as well as the VH/VV ratio, cross ratio, and interferometric coherence in VV, from agricultural fields. In this study, we use the decision support system for agrotechnology transfer (DSSAT) crop-growth simulation...
journal article 2023
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Shi, S. (author), Cheng, Xiaodong (author), Van den Hof, Paul M.J. (author)
Identifiability of a single module in a network of transfer functions is determined by whether a particular transfer function in the network can be uniquely distinguished within a network model set, on the basis of data. Whereas previous research has focused on the situations that all network signals are either excited or measured, we develop...
journal article 2023
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Cai, Cynthia (author), Meines, Siebren (author), Poon, Chris (author), Powałka, Leon (author), Xia, Yitong (author), YAN, LAN (author)
A 3D city model uses three-dimensional geometries to represent and model urban environments, in which the building model is the key feature. With the development of computer and data collection technologies, 3D city models are gaining growing capacities regarding storing rich information. This makes 3D city models more potentially useful than...
student report 2022
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Saeidian, Bahram (author), Rajabifard, Abbas (author), Atazadeh, Behnam (author), Kalantari, Mohsen (author)
Currently, many cities around the world use underground space for different applications such as tunnels, utility networks, parking, walkways, and shopping malls. Due to the increasing use of underground areas, management of this space is very important for decision-makers and stakeholders. A 3D Underground Land Administration (ULA) data model...
conference paper 2022
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Knödler, L. (author), Salmi, C. (author), Zhu, H. (author), Ferreira de Brito, B.F. (author), Alonso-Mora, J. (author)
Autonomous mobile robots require accurate human motion predictions to safely and efficiently navigate among pedestrians, whose behavior may adapt to environmental changes. This paper introduces a self-supervised continual learning framework to improve data-driven pedestrian prediction models online across various scenarios continuously. In...
journal article 2022
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Mulder, G. (author), van Leijen, F.J. (author), Barkmeijer, Jan (author), De Haan, Siebren (author), Hanssen, R.F. (author)
Numerical weather prediction (NWP) models are used to predict the weather based on current observations in combination with physical and mathematical models. Yet, they are limited by the spatial density and the accuracy of the available observations. Satellite radar interferometry (InSAR) is known to be extremely sensitive to the 3D...
journal article 2022
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Ottun, Abdul Rasheed (author), Mane, Pramod C. (author), Yin, Zhigang (author), Paul, Souvik (author), Liyanage, Mohan (author), Pridmore, Jason (author), Ding, Aaron Yi (author), Sharma, Rajesh (author), Nurmi, Petteri (author), Flores, Huber (author)
Federated learning (FL) is a promising privacy-preserving solution to build powerful AI models. In many FL scenarios, such as healthcare or smart city monitoring, the user's devices may lack the required capabilities to collect suitable data, which limits their contributions to the global model. We contribute social-aware federated learning...
journal article 2022
Searched for: subject%3A%22Data%255C+models%22
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