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Work20

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Dissertation19
Masters Thesis1

Creator

Altan, Ege1
Azcona, Emanuel Aquiles1
Chopp, Henry Hayashi1
Deng, Yu1
Díaz, Mark1
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Keyword

machine learning[remove]20
deep learning6
artificial intelligence2
image processing2
neural networks2
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Subject

Computer science4
Artificial intelligence3
Bioinformatics3
Biology2
Mechanical engineering2
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Language

en15

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Data Science Masters Theses1

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Dimensionality Reduction for Prosthetic Hand Control

Description:

In this document, I demonstrate that: 1) Linear basis functions cannot outperform nonlinear ones to represent hand kinematics 2) Nonlinear autoencoders outperform PCA on the dimensionality reduction of hand kinematics, 3) Nonlinear autoencoders outperform PCA in human gait representation and recurrent nonlinear autoencoders can seamlessly express the temporal dynamics, 4)...

Keyword:

kinematics, prosthetics, machine learning, gait, dimensionality reduction, and hand

Subject:

Engineering

Creator:

Portnova-Fahreeva, Alexandra

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

09/22/2022

Date Created:

2022-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:16176 and etdadmin_upload_920776
Advancing Computational Methods to Derive Insights from Real-world Health Data

Description:

In 2009, the Health Information Technology for Economic and Clinical Health Act (HITECH) promoted national use of electronic health records (EHR) in the US by giving incentives to providers who adopt ‘meaningful use’ of EHRs. As of 2017, nearly 86% of office-based physicians had adopted EHRs. EHRs have rich information...

Keyword:

computational phenotyping, real world evidence data, machine learning, biomedical informatics, deep learning, and electronic health records

Subject:

Bioinformatics

Creator:

Deng, Yu

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

09/22/2022

Date Created:

2022-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:15969 and etdadmin_upload_886066
Geometric deep learning in neuroimaging and human reward behavior

Description:

In recent years, machine learning on graphs (or networks) has gone from a niche topic with only a few active researchers worldwide, to a heavily invested field with novel use cases for dealing with relationships and/or interactions within complex systems in the natural and social sciences. Traditionally, choosing the right...

Keyword:

cognitive science, graph neural networks, machine learning, neuroimaging, image processing, and artificial intelligence

Subject:

Artificial intelligence, Electrical engineering, and Computer science

Creator:

Azcona, Emanuel Aquiles

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

09/22/2022

Date Created:

2022-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_922507 and http://dissertations.umi.com/northwestern:16184
Cut-and-Shuffle Mixing On a Hemispherical Shell and a Line Segment

Description:

Mixing by cutting-and-shuffling (like that for a deck of cards or a Rubik's cube) is a paradigm that has not been studied in detail even though it can be applied in a variety of situations including the mixing of granular materials. Mathematically, cutting- and-shuffling is described by piecewise isometries (PWIs),...

Keyword:

granular materials, mixing, machine learning, piecewise isometries, cutting-and-shuffling, and interval exchange transforms

Subject:

Applied mathematics, Chemical engineering, and Mechanical engineering

Creator:

Lynn, Thomas Ferguson

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

06/22/2022

Date Created:

2022-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_881325 and http://dissertations.umi.com/northwestern:15951
Deciphering the Geometry of Primary Motor Cortical Manifolds: Observations from Naturalistic Movements and Implications for Intracortical Brain-Computer Interfaces

Description:

Each neuron in the primary motor cortex (M1) is like a musician in an orchestra, contributing to a larger harmony under the constraint of a “neural manifold”—a geometric score describing the correlated signals produced by the neural musicians that drive movement. Despite the widespread recognition of the importance of M1...

Keyword:

neural networks, neural manifolds, motor control, machine learning, and brain-computer interface

Subject:

Biomedical engineering and Neurosciences

Creator:

Altan, Ege

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

08/23/2023

Date Created:

2023-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_1001502 and http://dissertations.umi.com/northwestern:16658
On Adaptive Time-Constrained Macro X-Ray Fluorescence Scanning and Analysis of Works of Art

Description:

In the late 2000’s, scientific studies in cultural heritage saw a great advancement in macro X-ray fluorescence (XRF) imaging of paintings. These images are used to generate elemental distribution maps, which aid in identifying chemical elements and paint pig- ments as well as their locations throughout the layers of the...

Keyword:

machine learning, x-ray fluorescence, and image processing

Subject:

Artificial intelligence, Materials Science, and Computer science

Creator:

Chopp, Henry Hayashi

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

08/23/2023

Date Created:

2023-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_998414 and http://dissertations.umi.com/northwestern:16642
Complex Exposures to Social Determinants of Health through Young Adulthood and Associations with Mid-life Cardiovascular Health and Events: The Coronary Artery Risk Development in Young Adults (CARDIA) Study

Description:

In the U.S., approximately 840,000 Americans die from cardiovascular disease (CVD) each year, and it is the leading cause of morbidity and mortality worldwide. The prevalence of CVD is on the rise and widespread disparities in CVD exist across economic, racial, and ethnic groups. In order to address the rising...

Keyword:

data science, informatics, machine learning, social determinants of health, and cardiovascular health

Subject:

Health sciences and Public health

Creator:

Zimmerman, Lindsay

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

10/07/2021

Date Created:

2021-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:15739 and etdadmin_upload_844529
Topics in Classification with Deep Learning

Description:

The task of classification has been increasingly attracting attention from researchers in recent years. The objective is to assign labels given attributes of samples. The classification task is practical in real-world applications and is widely explored in fields such as computer vision, natural language processing and information retrieval. The recent...

Keyword:

neural networks, classification, machine learning, and deep learning

Subject:

Artificial intelligence

Creator:

Xu, Yiming

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/01/2021

Date Created:

2020-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:15370 and etdadmin_upload_778963
Biases as Values: Evaluating Algorithms in Context

Description:

This dissertation asks how researchers can create more equitable algorithmic systems. Ultimately, this thesis explores methods and implications of representing subjects of analysis in the design and evaluation of algorithmic systems. I also unpack how algorithmic tools measure and quantify human behavior, giving heed to the potential impacts of these...

Keyword:

algorithms, machine learning, human-computer interaction, social discrimination, age discrimination, and algorithmic fairness

Subject:

Information science, Social research, and Computer science

Creator:

Díaz, Mark

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/01/2021

Date Created:

2020-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_762101 and http://dissertations.umi.com/northwestern:15226
Synergy of Physics and Learning-based Models in Computational Imaging and Display

Description:

Computational imaging (CI) is a class of imaging systems that optimize both the opto-electronic hardware and computing software to achieve task-specific improvements. Machine/deep learning models have proven effective in drawing statistical priors from adequate datasets. Yet when designing computational models for CI problems, physics-based models derived from the image formation...

Keyword:

computational imaging, machine learning, event-based vision, and holographic 3D display

Subject:

Optics and Computer science

Creator:

Wang, Zihao

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/01/2021

Date Created:

2020-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_763327 and http://dissertations.umi.com/northwestern:15240

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