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Identifying a gas source in turbulent environments presents a significant challenge for critical applications such as environmental monitoring and emergency response. This issue is addressed through an approach that combines distributed IoT…

Deep neural networks used for human detection are highly vulnerable to adversarial manipulation, creating safety and privacy risks in real surveillance environments. Wearable attacks offer a realistic threat model, yet existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Dingkun Zhou , Patrick P. K. Chan , Hengxu Wu , Shikang Zheng , Ruiqi Huang , Yuanjie Zhao

Diesel generators are emerging as community-initiated solutions to compensate for electricity shortage in cities marred by economical crisis and/or conflict. The resulting pollution distribution in dense urban environments is a major source…

Road user trajectory prediction in dynamic environments is a challenging but crucial task for various applications, such as autonomous driving. One of the main challenges in this domain is the multimodal nature of future trajectories…

Computer Vision and Pattern Recognition · Computer Science 2023-10-24 Younwoo Choi , Ray Coden Mercurius , Soheil Mohamad Alizadeh Shabestary , Amir Rasouli

Stealthy attacks on Industrial Control Systems can cause significant damage while evading detection. In this paper, instead of focusing on the detection of stealthy attacks, we aim to provide early warnings to operators, in order to avoid…

Cryptography and Security · Computer Science 2021-06-16 Mazen Azzam , Liliana Pasquale , Gregory Provan , Bashar Nuseibeh

This is a relevant problem because the design of most cities prioritizes the use of motorized vehicles, which has degraded air quality in recent years, having a negative effect on urban health. Modeling, predicting, and forecasting ambient…

Neural and Evolutionary Computing · Computer Science 2020-10-07 Jamal Toutouh

Global ambient air pollution, a transboundary challenge, is typically addressed through interventions relying on data from spatially sparse and heterogeneously placed monitoring stations. These stations often encounter temporal data gaps…

Machine Learning · Computer Science 2024-02-19 Liam J Berrisford , Hugo Barbosa , Ronaldo Menezes

Change point detection has become an important part of the analysis of the single-particle tracking data, as it allows one to identify moments, in which the motion patterns of observed particles undergo significant changes. The segmentation…

Quantitative Methods · Quantitative Biology 2025-06-23 Jakub Malinowski , Marcin Kostrzewa , Michał Balcerek , Weronika Tomczuk , Janusz Szwabiński

This paper proposes a novel joint channel-estimation and source-detection algorithm using successive interference cancellation (SIC)-aided generative score-based diffusion models. Prior work in this area focuses on massive MIMO scenarios,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Sagnik Bhattacharya , Muhammad Ahmed Mohsin , Kamyar Rajabalifardi , John M. Cioffi

This paper presents a time-domain implementation of the Method of Auxiliary Sources (MAS) combined with the Standard Impedance Boundary Condition (SIBC) for electromagnetic scattering problems involving cylindrical scatterers with finite…

Classical Physics · Physics 2026-01-13 Minas Kouroublakis , Nikolaos L. Tsitsas , Yehuda Leviatan

Extreme precipitation causes severe societal and economic damage, and weather control has long been discussed as a potential mitigation strategy. However, to the best of our knowledge, perturbation-based interventions for weather control…

Machine Learning · Computer Science 2026-05-15 Ayumu Ueyama , Kazuhiko Kawamoto , Hiroshi Kera

The identification of sources of advection-diffusion transport is based usually on solving complex ill-posed inverse models against the available state- variable data records. However, if there are several sources with different locations…

Machine Learning · Computer Science 2018-03-28 Valentin G. Stanev , Filip L. Iliev , Scott Hansen , Velimir V. Vesselinov , Boian S. Alexandrov

We study the problem of identifying the source of emerging large-scale outbreaks of foodborne disease. To solve the source identification problem we formulate a probabilistic model of the contamination diffusion process as a random walk on…

Physics and Society · Physics 2018-05-09 Abigail L. Horn , Hanno Friedrich

Many real-world systems modeled using partial differential equations (PDEs) involve unknown parameters that must be estimated from limited, noisy system observations. While typically assumed to be constants, some of these unobserved…

Methodology · Statistics 2025-08-19 Andrea Arnold

We propose enforcing constraints on Model-Based Diffusion by introducing emerging barrier functions inspired by interior point methods. We demonstrate that the standard Model-Based Diffusion algorithm can lead to catastrophic performance…

Robotics · Computer Science 2026-03-10 Raghav Mishra , Ian R. Manchester

Climate change poses increasingly complex challenges to our society. Extreme weather events such as floods, wild fires or droughts are becoming more frequent, spontaneous and difficult to foresee or counteract. In this work we specifically…

Machine Learning · Computer Science 2024-01-08 Teodor Chiaburu , Felix Biessmann

As a primary material frequently used in industry, chlorine is relatively easy to obtain and available even in large quantities. Despite its high toxicity, molecular chlorine is readily available since it is an essential educt in the…

Instrumentation and Detectors · Physics 2023-05-24 Arne Walter , Frank Wilsenack , Thomas Wolf , Frank Duschek

In this paper, we propose an online path planning architecture that extends the model predictive control (MPC) formulation to consider future location uncertainties for safer navigation through cluttered environments. Our algorithm combines…

Urban air pollution is a major environmental problem affecting human health and quality of life. Monitoring stations have been established to continuously obtain air quality information, but they do not cover all areas. Thus, there are…

Machine Learning · Computer Science 2021-08-17 Yuya Sasaki , Kei Harada , Shohei Yamasaki , Makoto Onizuka

Wildfires represent a problem for ecosystems, human activities, and economies, driven by the climate crisis and land-use changes. Predicting wildfire propagation through mathematical modelling is essential for damage mitigation and risk…