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Poddighe, R. (author), Roos, N. (author)
In this paper, two alternative methods to the Inverse Kinematics problem are compared to traditional methods regarding computation time, accuracy, and convergence rate. The test domain is the arm of the NAO humanoid robot. The results show that FABRIK, a heuristic iterative approximation algorithm outperforms the two traditional methods, which...
conference paper 2013
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OUYANG, Boya (author), LI, Yuhai (author), SONG, Yu (author), WU, Feishu (author), YU, Huizi (author), WANG, Yongzhe (author), BAUCHY, Mathieu (author), SANT, Gaurav (author)
Despite previous efforts to relate concrete proportioning and strength, a robust knowledgebased model for accurate concrete strength predictions is still lacking. As an alternative to physical or chemical-based models, machine learning (ML) methods offer a new solution to this problem. Although ML can handle the complex, non-linear, non-additive...
conference paper 2021
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Khoshelham, K. (author), Nardinocchi, C. (author)
This paper presents a learning Dempster-Shafer model for the detection of buildings in aerial image and range data. The process of evidence assignment in the Dempster-Shafer method is implemented through membership functions in an adaptive network-based fuzzy inference system, where a back propagation learning rule is employed to tune the...
conference paper 2009
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Saldaña Ochoa, Karla (author), Comes, M. (author)
Along with climate change, more frequent extreme events, such as flooding and tropical cyclones, threaten the livelihoods and wellbeing of poor and vulnerable populations. One of the most immediate needs of people affected by a disaster is finding shelter. While the proliferation of data on disasters is already helping to save lives, identifying...
conference paper 2021
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Hajee, Bram (author), Wisse, Kees (author), Mohajerin Esfahani, P. (author)
Multi-sensor networks are becoming more and more popular in order to assess the post-occupancy performance of smart buildings, since they enable continuous monitoring with a high spatial resolution of the occupancy, thermal comfort and indoor air quality. An urgent, but poorly attended topic in this field is the automated detection of sensor...
conference paper 2022
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Kayastha, N. (author), Solomatine, D.P. (author), Lal Shrestha, D. (author)
In the MLUE method (reported in Shrestha et al. [1, 2]) we run a hydrological model M for multiple realizations of parameters vectors (Monte Carlo simulations), and use this data to build a machine learning model V to predict uncertainty (quantiles) of the model M output. In this paper, for model V, we employ three machine learning techniques,...
conference paper 2014
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Biljecki, F. (author), Sindram, M. (author)
Building datasets (e.g. footprints in OpenStreetMap and 3D city models) are becoming increasingly available worldwide. However, the thematic (attribute) aspect is not always given attention, as many of such datasets are lacking in completeness of attributes. A prominent attribute of buildings is the year of construction, which is useful for some...
conference paper 2017
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de Jong, M. (author), Mavridis, P. (author), Aroyo, Lora (author), Bozzon, A. (author), Vos, Jesse de (author), Oomen, Johan (author), Dimitrova, Antoaneta (author), Badenoch, Alec (author)
In this project we explore the presence of ambiguity in textual and visual media and its influence on accurately understanding and<br/>capturing bias in news. We study this topic in the context of supporting<br/>media scholars and social scientists in their media analysis. Our focus<br/>lies on racial and gender bias as well as framing and the...
conference paper 2018
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Sun, Junzi (author), Ellerbroek, Joost (author), Hoekstra, J.M. (author)
With the increasing availability of ADS-B transponders on commercial aircraft, as well as the rapidly growing deployment of ground stations that provide public access to their data, accessing open aircraft flight data is becoming easier for researchers. Given the large number of operational aircraft, significant amounts of flight data can be...
conference paper 2016
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Sun, W. (author), Katsifodimos, A (author), Hai, R. (author)
The rapid growth of large-scale machine learning (ML) models has led numerous commercial companies to utilize ML models for generating predictive results to help business decision-making. As two primary components in traditional predictive pipelines, data processing, and model predictions often operate in separate execution environments,...
conference paper 2023
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de Hoop, S. (author), Voskov, D.V. (author)
The main objective of this study is to perform Uncertainty Quantification (UQ) using a detailed representation of fractured reservoirs. This is achieved by creating a simplified representation of the fracture network while preserving the main characteristics of the high-fidelity model. We include information at different scales in the UQ...
conference paper 2021
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Hadjisotiriou, George (author), Mansour Pour, K. (author), Voskov, D.V. (author)
In this study, we utilize deep neural networks to approximate operators of a nonlinear partial differential equation (PDE), within the Operator-Based Linearization (OBL) simulation framework, and discover the physical space for a physics-based proxy model with reduced degrees of freedom. In our methodology, observations from a high-fidelity...
conference paper 2023
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Pinasco, Silvia (author), Lagomarsino, Sergio (author), Carocci, Caterina (author), Coraddu, A. (author), Oneto, Luca (author), Cattari, Serena (author)
Seismic events in Italy and worldwide have highlighted the high vulnerability of unreinforced masonry (URM) structures in small historical centres. A key feature of these settlements is to be mostly composed of buildings in aggregate, i.e., interconnected by a more or less structurally effective connection. The seismic assessment of such...
conference paper 2023
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Han, Y. (author), Yarovoy, Alexander (author), Fioranelli, F. (author)
This research aims to develop a contactless, radar-based sleep apnea detection method. A novel identification approach for this is proposed, based on the envelope of UWB radar spectrograms and machine learning. The envelope of the spectrogram is extracted by an image-based method, followed by signal smoothing via variational mode decomposition ...
conference paper 2022
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Sayin, Burcu (author), Yang, J. (author), Passerini, Andrea (author), Casati, Fabio (author)
In this paper, we argue that the way we have been training and evaluating ML models has largely forgotten the fact that they are applied in an organization or societal context as they provide value to people. We show that with this perspective we fundamentally change how we evaluate and select machine learning models.
conference paper 2023
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Fioranelli, F. (author), Guendel, Ronny (author), Kruse, N.C. (author), Yarovoy, Alexander (author)
Driven by its contactless sensing capabilities and the lack of optical images being recorded, radar technology has been recently investigated in the context of human healthcare. This includes a broad range of applications, such as human activity classification, fall detection, gait and mobility analysis, and monitoring of vital signs such as...
conference paper 2023
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Verhoeven, Gijs (author), Vergara Barrios, P.P. (author), Salazar Duque, Edgar Mauricio (author), Kok, Koen (author)
To guarantee a successful deployment of a droop-based control strategy to mitigate overvoltage problems caused by solar photovoltaic (PV) generation, Distribution System Operators (DSOs) will need to estimate the amount of active power curtailed by the PV inverters for billing purposes. This paper provides a structural elaboration on the...
conference paper 2022
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Guendel, Ronny (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
In this paper, we investigate the classification of Activities of Daily Living (ADL) by using a pulsed ultra-wideband radar. Specifically, we focus on contiguous activities that can be inseparable in time and share a common transition, such as walking and falling. The range-time data domain is deliberately exploited to determine transitions from...
conference paper 2020
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Li, Haobo (author), Le Kernec, Julien (author), Mehul, Ajay (author), Fioranelli, F. (author)
This paper discusses a fusion framework with data from multiple, distributed radar sensors based on conventional classifiers, and transfer learning with pre-trained deep networks. The application considered is the classification of gait styles and the detection of critical accidents such as falls. The data were collected from a network comprised...
conference paper 2020
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Hendrickx, Rik (author), Zoutendijk, M. (author), Mitici, M.A. (author), Schäfer, Jeffrey (author)
A key part of efficient airport operational planning is to have insight into potential flight delays and cancellations. For airport planners, it is important to obtain flight delay or cancellation predictions with a high degree of certainty, i.e. a high precision. This allows planners to make sound decisions based on these predictions. To obtain...
conference paper 2021
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