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In chemical processing and bioprocessing, conventional online sensors are limited to measure only basic process variables like pressure and temperature, pH, dissolved O and CO$_2$ and viable cell density (VCD). The concentration of other…

Quantitative Methods · Quantitative Biology 2020-05-07 Semion Rozov

Having a precise knowledge of the dispersal ability of a population in a heterogeneous environment is of critical importance in agroecology and conservation biology as it can provide management tools to limit the effects of pests or to…

Populations and Evolution · Quantitative Biology 2015-03-19 L. Roques , E. Walker , P. Franck , S. Soubeyrand , E. K. Klein

We study identification and estimation of the average treatment effect in a correlated random coefficients model that allows for first stage heterogeneity and binary instruments. The model also allows for multiple endogenous variables and…

Methodology · Statistics 2014-01-03 Matthew A. Masten , Alexander Torgovitsky

Developing a rapid, but also reliable and efficient, method for classifying the seismic damage potential of buildings constructed in countries with regions of high seismicity is always at the forefront of modern scientific research. Such a…

Machine Learning · Computer Science 2022-05-03 Konstantinos Kostinakis , Konstantinos Morfidis , Konstantinos Demertzis , Lazaros Iliadis

Multipaths, reflections, diffractions, and material interactions complicate indoor wireless propagation modelling. More than 80% of wireless data is consumed indoors; hence, planning successful deployments and maximizing network performance…

Energy conservation in buildings is a paramount concern to combat greenhouse gas emissions and combat climate change. The efficient management of room occupancy, involving actions like lighting control and climate adjustment, is a pivotal…

Machine Learning · Computer Science 2023-12-25 Siqi Mao , Yaping Yuan , Yinpu Li , Ziren Wang , Yuanxin Yao , Yixin Kang

To encourage further research and to facilitate fair comparisons in the development of deep learning-based radio propagation models, in the less explored case of directional radio signal emissions in indoor propagation environments, we have…

Signal Processing · Electrical Eng. & Systems 2025-01-24 Stefanos Bakirtzis , Çağkan Yapar , Kehai Qiu , Ian Wassell , Jie Zhang

$^{222}Rn$ emanating from environmental dust constitutes an important background component for many low-energy, low-rate experiments. Radon emanation rates from dust and rock, thus, are important for experiment planning. In this paper, we…

Instrumentation and Detectors · Physics 2022-10-24 Yue Meng , Jerry Busenitz , Andreas Piepke , Raymond Tsang , Mengmeng Wu , Yukun Yao

Room geometry inference algorithms rely on the localization of acoustic reflectors to identify boundary surfaces of an enclosure. Rooms with highly absorptive walls or walls at large distances from the measurement setup pose challenges for…

Audio and Speech Processing · Electrical Eng. & Systems 2024-02-12 H. Nazim Bicer , Cagdas Tuna , Andreas Walther , Emanuël A. P. Habets

Respiratory diseases impose a significant burden on global health, with current diagnostic and management practices primarily reliant on specialist clinical testing. This work aims to develop machine learning-based algorithms to facilitate…

Machine Learning · Computer Science 2024-09-06 Negar Orangi-Fard , Alexandru Bogdan , Hersh Sagreiya

Digital maps will revolutionize our experience of perceiving and navigating indoor environments. While today we rely only on the representation of the outdoors, the mapping of indoors is mainly a part of the traditional SLAM problem where…

Signal Processing · Electrical Eng. & Systems 2019-10-29 Anna Guerra , Francesco Guidi , Gianni Pasolini , Antonio Clemente , Raffaele D'Errico , Davide Dardari

Exposure to poor indoor air quality poses significant health risks, necessitating thorough assessment to mitigate associated dangers. This study aims to predict hourly indoor fine particulate matter (PM2.5) concentrations and investigate…

Machine Learning · Computer Science 2024-05-14 Wenhua Yu , Bahareh Nakisa , Seng W. Loke , Svetlana Stevanovic , Yuming Guo , Mohammad Naim Rastgoo

Ground-penetrating radar (GPR) has been used as a non-destructive tool for tree root inspection. Estimating root-related parameters from GPR radargrams greatly facilitates root health monitoring and imaging. However, the task of estimating…

Computer Vision and Pattern Recognition · Computer Science 2021-12-28 Hai-Han Sun , Yee Hui Lee , Qiqi Dai , Chongyi Li , Genevieve Ow , Mohamed Lokman Mohd Yusof , Abdulkadir C. Yucel

This paper introduces a novel methodology for generating controlled, multi-level dust concentrations in a highly cluttered environment representative of harsh, enclosed environments, such as underground mines, road tunnels, or collapsed…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Zhenan Liu , Yaodong Cui , Amir Khajepour , George Shaker

Probabilistic collision detection (PCD) is essential in motion planning for robots operating in unstructured environments, where considering sensing uncertainty helps prevent damage. Existing PCD methods mainly used simplified geometric…

Robotics · Computer Science 2025-08-28 Xiaoli Wang , Sipu Ruan , Xin Meng , Gregory Chirikjian

Method of parameterizing and smoothing the unknown underling distributions using Bernstein polynomials is proposed, verified and investigated. Any distribution with bounded and smooth enough density can be approximated by the proposed…

Methodology · Statistics 2015-06-23 Zhong Guan

Distributionally robust optimization (DRO) has become a powerful framework for estimation under uncertainty, offering strong out-of-sample performance and principled regularization. In this paper, we propose a DRO-based method for linear…

Machine Learning · Statistics 2025-05-06 Liviu Aolaritei , Soroosh Shafiee , Florian Dörfler

This work reports on a measurement study to estimate the attenuation of 450 MHz LTE networks. The LTE band 72 is currently deployed in Germany, in particular for smart grid applications. Due to this use-case, we assume that a significant…

Networking and Internet Architecture · Computer Science 2024-05-16 Christian Sorgatz , Christian Lüders , Michael Rademacher

As the use of automotive radar increases, performance limitations associated with radar-to-radar interference will become more significant. In this paper we employ tools from stochastic geometry to characterize the statistics of radar…

Information Theory · Computer Science 2016-07-11 Akram Al-Hourani , Robin J. Evans , Sithamparanathan Kandeepan , Bill Moran , Hamid Eltom

Analyses of occurrences of residential burglary in urban areas have shown that crime rates are not spatially homogeneous: rates vary across the network of city streets, resulting in some areas being far more susceptible to crime than…

Applications · Statistics 2024-04-02 Elizabeth Upton , Luis Carvalho