10.4231/SCF2-QJ02
Koushiki Basu
,
Nicholas Huls
,
Shan Lu
,
Tonglei Li
11/06/2024
We implemented the Manifold Embedding of Molecular Surface approach, which retains the quantum mechanical characteristics of molecules, to predict a drug's likelihood of binding to cytochrome P450 enzymes by deep learning.
deep learning Informatics Machine Learning Molecular Pharmacology
10.4231/Q0HY-AT09
Ahmed Khaled Soliman
,
Andres Torres
,
Chang Heon Lee
,
Guilherme A. Ribeiro
,
Li-fan Wu
,
Mo Rastgaar
05/16/2022
Estimating gait realtime through 2 wearable sensors and a PCA based linear regression model.
Acceleration Biomedical Engineering Machine Learning Mechanical Engineering PCA Robotics Stepwise Multiple linear Regression Wearable Device
10.4231/AMGQ-0T59
Itamar Roth
,
Jan Allebach
,
Jiayin Liu
,
Orel Bat Mor
,
Oren Haik
,
Shani Gat
,
Tal Frank
,
Yitzhak Yitzhaky
06/01/2022
This dataset contains two parts: one has halftone patches that were used to predicts the quality level and scale using machine learning methods. The second part contains full versions of halftone images so viewers can zoom in to see the details.
direct binary search Electrical and Computer Engineering Halftone screen Machine Learning
10.4231/4K64-4818
Charles Fieseler
,
Chven Mitchell
,
Laura J Pyrak-Nolte
,
Nathan Kutz
06/14/2022
Acoustic waveforms collected during the monitoring of moisture loss in synthetic rock samples composed of mortar, and mortar with either distributed clay or localized clay, under ambient laboratory conditions.
acoustic signals clay cracking Fractures Machine Learning Physics
10.4231/1TZX-BR43
David R Johnson
,
Ed Delp
,
Fu-Chen Chen
,
Mohammad Jahanshahi
07/28/2020
Structural attributes relevant to flood risk (foundation height/type, square footage, number of stories, building type), produced using machine learning for automated image analysis of GSV images.
flood risk Industrial Engineering Machine Learning structure attributes
10.4231/E80W-7941
Aihua Huang
,
John W. Sutherland
,
Sidi Deng
,
Xiaoyu Zhou
,
Yuehwern Yih
09/03/2020
This repository contains the supporting information for the manuscript regarding Sherwood principle and Machine learning. All critical underlying data files, along with a flow chart that describes the methodologies applied in the paper are enclosed.
Circular Economy Empirical Models Environmental and Ecological Engineering Machine Learning Sherwood Principle
10.4231/0A0F-7A84
10/14/2019
This project works on understanding the different statistical models that are available to analyze and predict mean sea level changes in Guam.
Climate Change Data Education Earth and Atmospheric Sciences FAIR Data Machine Learning Sea level rise Statistical analysis Statistical Methods
10.4231/3YX4-EY30
01/21/2020
Source code of an ANN model, site level data, input data, output data and visualization results, which are presented in the manuscript "Inventorying Global Wetland Methane Emissions Based on In Situ Data and an Artificial Neural Network...
Artificial Neural Network (ANN) Atmospheric Chemistry Modeling Biogeochemistry Earth and Atmospheric Sciences Interactive Data Language (IDL) Machine Learning Matlab Methane Dynamics Model (MDM) Methane Emission
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