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[Submitted on 21 Nov 2024] View a PDF of the paper titled Predictive Maintenance Study for High-Pressure Industrial Compressors: Hybrid Clustering Models, by Alessandro Costa and 4 other authors View PDF HTML (experimental) Abstract:This study introduces a predictive maintenance strategy for high pressure industrial compressors using sensor data and features derived from unsupervised clustering integrated into classification models. The goal is to enhance model accuracy and efficiency in detecting compressor failures. After data pre processing, sensitive clustering parameters were tuned to identify algorithms that best capture the dataset's temporal and operational characteristics. Clustering algorithms were evaluated using quality metrics like…

[Submitted on 21 Mar 2024 (v1), last revised 21 Nov 2024 (this version, v2)] View a PDF of the paper titled Exosense: A Vision-Based Scene Understanding System For Exoskeletons, by Jianeng Wang and 7 other authors View PDF HTML (experimental) Abstract:Self-balancing exoskeletons are a key enabling technology for individuals with mobility impairments. While the current challenges focus on human-compliant hardware and control, unlocking their use for daily activities requires a scene perception system. In this work, we present Exosense, a vision-centric scene understanding system for self-balancing exoskeletons. We introduce a multi-sensor visual-inertial mapping device as well as a navigation stack…

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[Submitted on 4 Jun 2024 (v1), last revised 21 Nov 2024 (this version, v2)] View a PDF of the paper titled Integrating Physics of the Problem into Data-Driven Methods to Enhance Elastic Full-Waveform Inversion with Uncertainty Quantification, by Vahid Negahdari and 2 other authors View PDF HTML (experimental) Abstract:Full-Waveform Inversion (FWI) is a nonlinear iterative seismic imaging technique that, by reducing the misfit between recorded and predicted seismic waveforms, can produce detailed estimates of subsurface geophysical properties. Nevertheless, the strong nonlinearity of FWI can trap the optimization in local minima. This issue arises due to factors such as improper initial…

arXiv:2411.13716v1 Announce Type: new Abstract: Gait analysis using computer vision is an emerging field in AI, offering clinicians an objective, multi-feature approach to analyse complex movements. Despite its promise, current applications using RGB video data alone are limited in measuring clinically relevant spatial and temporal kinematics and establishing normative parameters essential for identifying movement abnormalities within a gait cycle. This paper presents a data-driven method using RGB video data and 2D human pose estimation for developing normative kinematic gait parameters. By analysing joint angles, an established kinematic measure in biomechanics and clinical practice, we aim to enhance gait analysis capabilities…

[Submitted on 9 Oct 2022 (v1), last revised 21 Nov 2024 (this version, v3)] View a PDF of the paper titled Fine-Grained Detection of Solidarity for Women and Migrants in 155 Years of German Parliamentary Debates, by Aida Kostikova and 5 other authors View PDF HTML (experimental) Abstract:Solidarity is a crucial concept to understand social relations in societies. In this paper, we explore fine-grained solidarity frames to study solidarity towards women and migrants in German parliamentary debates between 1867 and 2022. Using 2,864 manually annotated text snippets (with a cost exceeding 18k Euro), we evaluate large language models (LLMs) like…