Nettsider med emneord «Time series»
Devices, like smart-watches, that can collect health data from "everybody" all the time, and machine learning (ML) to analyze this data will strongly impact future health solutions.
Digital twins are necessary for the successful digitalization of oil and gas field operations. Unfortunately, they are poorly understood and hyped.
In Permafrost4Life, we investigate how permafrost is entangled with ecosystems and the traditional herder lifestyle important for the Mongolian society.
The recent summer drought events in Europe and their associated devastating wildfires highlight the importance of understanding and predicting such extreme events and their impact.
In MASSIVE, the project team aims at improving glacier mapping and surface glacier mass balance estimation techniques with the help of machine learning, especially deep learning. We will develop the methodology for glaciers in Norway, Svalbard, the European Alps and the Himalayas and then expand it to regions with different glacier characteristics.
LATICE aims to advance the knowledge base concerning land atmosphere interactions through improved model representation of snow, permafrost, hydrology and large-scale vegetation processes representative of high latitudes, including; 1) New ground observations (gap filling using ML); 2) Land surface model parametrization using data science methods; 3) Seasonal snow cover dynamics using data assimilation and Earth observations (e.g. satellite data, drones).
The CryoGrid community model is a flexible toolbox for simulating the ground thermal regime and the ice/water balance for permafrost and glaciers. The CryoGrid community model can accommodate a wide variety of application scenarios, which is achieved by fully modular structures through object-oriented programming.
UiO:RealArt will use artificial world data to study the real-world problem of safe medication use in pregnancy.
Colorectal cancer (CRC) symptoms are unspecific – often
emerging when the disease is no longer curable. Screening
reduces CRC mortality, but current screening tests need improvement to be more accurate and less costly and invasive. The overall aim of the CRCbiome study is to discover gut microbiota biomarkers for colorectal cancer screening.
For maritime safety surveillance we develop new approaches
based on the availability of large arrays of sensors, which
monitor condition and performance of vessels, machinery, or
power systems.
In a wide range of applications, monitoring data streams for faults or changes in behavior (called anomalies) is of great importance.
BigInsight produces innovative solutions for key data-driven challenges facing our consortium of private, public and research partners, by developing original statistical and machine learning methodologies.
The main objective of this project is to provide a geoscientific solution for increasing the renewable (geothermal) energy production in northwest Romania. This will lead to a decrease in actual CO2 emissions generated by electrical and thermal energy production using fossil fuel.
Recent advances in ultrashort laser technology allow us to probe and potentially control molecules and chemical reactions at the level of electrons.
The dynamics of Chemical Reaction Networks (CRN), which are typically embedded within Mass and Energy Transport Phenomena such as diffusion or advection, govern the performance of innumerable industrial technologies.
SPATUS is a Thematic Research Group funded by UiO:Energy.
Snow in the mountains is a source for drinking water, hydropower, irrigation, but can also cause floods and geohazards. There are currently no efficient methods to measure depth of snow in mountains and remote areas.