Related papers: Tokyo Kion-On: Query-Based Generative Sonification…
This paper presents a cloud-connected indoor air quality sensor system that can be deployed to patients' homes to study personal microenvironmental exposure for asthma research and management. The system consists of multiple compact sensor…
This paper describes the development of a system that enables real time data visualization via a webapp regarding sound intensity using multiple node devices connected through internet. The prototypes were realized using ATmega328 (Arduino…
In the context of Cosmic Microwave Background data analysis, we study the solution to the equation that transforms scanning data into a map. As originally suggested in "messenger" methods for solving linear systems, we split the noise…
[Abridged] This paper describes the creation of HadISD: an automatically quality-controlled synoptic resolution dataset of temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud cover from global weather…
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…
Since 2019, three scintillator detectors of the EEE collaboration have been continuously measuring cosmic muon rates at 78.9{\deg}N at the Ny-{\AA}lesund Research Station (Svalbard). The resulting six-year time series reveals a pronounced…
With the development of industrialization, air pollution is also steadily on the rise since both industrial and daily activities generate a massive amount of air pollution. Since decreasing air pollution is critical for citizens' health and…
Remote sensing observations of the Earth's surface are frequently stymied by clouds, water vapour, and aerosols in our atmosphere. These degrade or preclude the measurementof quantities critical to scientific and, hence, societal…
Monitoring remote forests is a global challenge central to climate mitigation and biodiversity conservation, yet satellite observations are frequently limited by weather, dense canopies, and solar dependency. Here we show that passive…
Ground-level ozone in Kiev for an episode of its high concentration in August 2000 was simulated with the model of the urban air pollution UAM-V (Urban Airshed Model). The study of total ozone over Kiev and its concentration changes with…
Here we find the increase in 1/f noise of superconducting resonators at low temperatures to be completely incompatible with the standard tunneling model (STM) of Two Level Systems (TLS), which has been used to describe low-frequency noise…
Accurate weather forecasting is of paramount importance for a wide range of practical applications, drawing substantial scientific and societal interest. However, the intricacies of weather systems pose substantial challenges to accurate…
With the press of global climate change, extreme weather and sudden weather changes are becoming increasingly common. To maintain a comfortable indoor environment and minimize the contribution of the building to climate change as much as…
Reliable weather forecasting is of great importance in science, business, and society. The best performing data-driven models for weather prediction tasks rely on recurrent or convolutional neural networks, where some of which incorporate…
Efficient air quality sensing serves as one of the essential services provided in any recent smart city. Mostly facilitated by sparsely deployed Air Quality Monitoring Stations (AQMSs) that are difficult to install and maintain, the overall…
Thermal comfort is essential for well-being in urban spaces, especially as cities face increasing heat from urbanization and climate change. Existing thermal comfort models usually overlook temporal dynamics alongside spatial dependencies.…
Policymakers frequently analyze air quality and climate change in isolation, disregarding their interactions. This study explores the influence of specific climate factors on air quality by contrasting a regression model with K-Means…
With the Thomson scattering (TS) system in KSTAR, temporal evolution of electron temperature ($T_e$) is estimated using a weighted look-up table method with fast sampling ($1.25$ or $2.5$ GS/s) digitizers during the 2014 KSTAR campaign.…
The sea surface temperature (SST), a key environmental parameter, is crucial to optimizing production planning, making its accurate prediction a vital research topic. However, the inherent nonlinearity of the marine dynamic system presents…
A nonanticipative analog method is used for the long-term forecast of air temperature extremes. The data to be used for prediction include average daily air temperature, mean visibility, mean wind speed, mean dew point, maximum and minimum…