Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Aeromedical Evacuation (AE) medical crews. The goal of the project is to embed interactive software algorithms, derived from Aeromedical Evacuation Clinical Protocols (AECPs), directly into the provider's
-
areas. These include, but are not limited to: Applying machine learning algorithms to solve real-world problems. Creating and structuring databases for storage, retrieval, and image analysis. Determining
-
applications and methods Gaining experience with Qubit coupling schemes including hetero – qubit ensembles Designing Qubit cross – talk mitigation techniques Applying Quantum algorithms for small to medium scale
-
be focused on learning how to develop algorithms, performing biochar characterization tests, and characterizing microbial communities that colonize biochar in different ecosystems. Learning Objectives
-
to participate and gain knowledge in researching existing topography, wave, water level, ecological, and sediment transport data from the laboratory and/or field to validate existing models and test algorithm
-
epidemiologic patterns as swine IAV is transmitted among hosts and across landscapes will be quantified. The participant may also have the opportunity to be involved in the development of novel algorithms
-
be focused on learning how to develop algorithms, performing biochar characterization tests, and characterizing microbial communities that colonize biochar in different ecosystems. Learning Objectives
-
. The participant may also have the opportunity to be involved with the development of novel algorithms, bioinformatic tools or analytical pipelines that quantify the diversity of RNA viruses that may be deployed in
-
validate algorithms for estimating heat stress, counting animals, and estimating mass in real-time. Although research is needed to integrate One Health assessments across the soil-pasture-animal continuum
-
to develop novel statistical techniques, analyze satellite and other remote sensing data, implement machine learning algorithms, assess numerical model performance, improve risk assessment tools, and deepen