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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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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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Alfrink, Kars (author), Keller, A.I. (author), Doorn, N. (author), Kortuem, G.W. (author)
Local governments increasingly use artificial intelligence (AI) for automated decision-making. Contestability, making systems responsive to dispute, is a way to ensure they respect human rights to autonomy and dignity. We investigate the design of public urban AI systems for contestability through the example of camera cars: human-driven...
conference paper 2023
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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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Kruse, N.C. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Due to numerous benefits, radar is considered as an important sensor for human activity classification. The problem of classifying continuous sequences of activities of unconstrained duration has been studied in this work. To tackle this challenge, a radar data processing method utilizing point transformer networks has been proposed. The method...
conference paper 2023
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Al-Ars, Z. (author), Agba, Obinna (author), Guo, Zhuoran (author), Boerkamp, C. (author), Jaber, Ziyaad (author), Jaber, Tareq (author)
This paper offers a systematic method for creating medical knowledge-grounded patient records for use in activities involving differential diagnosis. Additionally, an assessment of machine learning models that can differentiate between various conditions based on given symptoms is also provided. We use a public disease-symptom data source called...
conference paper 2023
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Tricomi, Pier Paolo (author), Facciolo, Lisa (author), Apruzzese, Giovanni (author), Conti, M. (author)
Did you know that over 70 million of Dota2 players have their in-game data freely accessible? What if such data is used in malicious ways? This paper is the first to investigate such a problem. Motivated by the widespread popularity of video games, we propose the first threat model for Attribute Inference Attacks (AIA) in the Dota2 context....
conference paper 2023
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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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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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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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Verduzco, Alejandro (author), Páramo Balsa, Paula (author), Gonzalez-Longatt, Francisco (author), Andrade, Manuel A. (author), Acosta Montalvo, Martha Nohemi (author), Rueda, José L. (author), Palensky, P. (author)
This research paper presents a method that uses measurements of voltages angles, as provided by phasor measurement units (PMU), to accurately detect the sudden disconnection of a generation unit from a power grid. Results in this research paper have demonstrated, in a practical fashion, that a multi-layer perceptron (MLP) neural network (NN) can...
conference paper 2022
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Köylü, T.C. (author), Hamdioui, S. (author), Taouil, M. (author)
Artificial neural networks (ANNs) are used to accomplish a variety of tasks, including safety critical ones. Hence, it is important to protect them against faults that can influence decisions during operation. In this paper, we propose smart and low-cost redundancy schemes that protect the most vulnerable ANN parts against fault attacks....
conference paper 2022
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Van Oort, Bart (author), Cruz, Luis (author), Loni, Babak (author), van Deursen, A. (author)
Machine Learning (ML) projects incur novel challenges in their development and productionisation over traditional software applications, though established principles and best practices in ensuring the project's software quality still apply. While using static analysis to catch code smells has been shown to improve software quality attributes...
conference paper 2022
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Chen, Peiran (author), Calis, Metin (author), Wijkstra, Hessel (author), Huang, Pintong (author), Hunyadi, Borbala (author), Mischi, Massimo (author)
A cost-effective, widely available, and practical diagnostic imaging tool for prostate cancer (PCa) localization is still lacking. Recently, the contrast-ultrasound dispersion imaging (CUDI) technique has been developed for PCa localization by quantifying dynamic contrast-enhanced ultrasound (DCE-US) acquisitions. Tissue stiffness is an...
conference paper 2022
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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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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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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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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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