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Now showing items 51-59 of 59
Search for third generation vector-like leptons with the ATLAS detector
(2022-03-09)
The Standard Model of particle physics provides a concise description of the building blocks of our universe in terms of fundamental particles and their interactions. It is an extremely successful theory, providing a ...
Machine Learning Algorithms and Applications in Investment Analysis
(2016-12-16)
We can simplify investment analysis as filtering out speculative stocks, bonds, derivatives and other financial products. This area is very challenging yet extremely critical since individual investors’, large institutions’ ...
Single-probe Mass Spectrometry Imaging: Applications and Advanced Data Analysis
(2019-12)
Mass spectrometry imaging (MSI) is becoming a powerful tool in the bioanalytical studies owing to its unique capability to sensitively map the spatial distribution of broad ranges of molecules on biological samples. Due ...
Interpretable deep neural networks for more accurate predictive genomics and genome-wide association studies
(2023-05)
Genome-wide association studies (GWAS) and predictive genomics have become increasingly important in genetics research over the past decade. GWAS involves the analysis of the entire genome of a large group of individuals ...
Machine Learning for Impact-Based Flash Flood Warnings: Hazard Report Operationalization for Impact Predictions
(2023-12-15)
Floods account for approximately one third of all global geophysical hazards, and flash floods allow for extremely short lead times for warnings to be emitted. Flash flood warnings are weather-related alerts which serve ...
National Performance Management Research Dataset (NPMRDS) - Speed Validation for Traffic Performance Measures (FHWA-OK-17-02)
(Oct-17)
This report presents research detailing the use of the first version of the National Performance Management Research Data Set (NPMRDS v.1) comprised of highway vehicle travel times used for computing performance measurements ...
DATA-DRIVEN REAL-TIME GEOSTEERING USING SURFACE DRILLING DATA
(2019-12-13)
In this thesis I present a method for estimating lithology or deriving formation properties from real-time surface drilling data. This information can then be used to enhance real-time geosteering capabilities. Current ...
Storm-scale Ensemble-based Severe Weather Guidance: Development of an Object-based Verification Framework and Applications of Machine Learning
(2020-12-18)
A goal of the National Oceanic and Atmospheric Administration (NOAA) Warn-on-Forecast (WoF) project is to provide rapidly updating probabilistic guidance to human forecasters for short-term (e.g., 0-3 h) severe weather ...
A Machine Learning Based Multi-model ensemble Approach to reconstruct the historical monthly precipitation over Oklahoma using NOAA's SPEAR dataset
(2024-05-10)
General Circulation Models (GCMs) are important tools in simulating and projecting future precipitation at the decadal scale. However, it is inevitable that simulation and projection errors and uncertainty exist in GCMs, ...