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Estimation Of Multi-Directional Ankle Impedance As A Function Of Lower Extremity Muscle Activation, Lauren Knop Jan 2019

Estimation Of Multi-Directional Ankle Impedance As A Function Of Lower Extremity Muscle Activation, Lauren Knop

Dissertations, Master's Theses and Master's Reports

The purpose of this research is to investigate the relationship between the mechanical impedance of the human ankle and the corresponding lower extremity muscle activity. Three experimental studies were performed to measure the ankle impedance about multiple degrees of freedom (DOF), while the ankle was subjected to different loading conditions and different levels of muscle activity. The first study determined the non-loaded ankle impedance in the sagittal, frontal, and transverse anatomical planes while the ankle was suspended above the ground. The subjects actively co-contracted their agonist and antagonistic muscles to various levels, measured using electromyography (EMG). An Artificial Neural Network ...


Applying Computer Vision For Detection Of Diseases In Plants, Xuan Truong Tran Jan 2019

Applying Computer Vision For Detection Of Diseases In Plants, Xuan Truong Tran

Graduate Theses and Dissertations

Early detection and quantification of diseases in food plants are critical to agriculture industry and national food security. However, limitation in technology and cost has limited the success of applying Computer Vision in Plant Science. This research builds on the recent advance of Machine Learning, GPU and smartphones to tackle the problem of fast and low cost diagnosis of plant disease. In particular, we choose soybean as the subject for applying automatic disease detection. The reason is because soybean is an important crop for the state of Iowa and an important source of food for America. The plant is however ...


Machine Learning Assisted Optimization With Applications To Diesel Engine Optimization With The Particle Swarm Optimization Algorithm, Aaron M. Bertram Jan 2019

Machine Learning Assisted Optimization With Applications To Diesel Engine Optimization With The Particle Swarm Optimization Algorithm, Aaron M. Bertram

Graduate Theses and Dissertations

A novel approach to incorporating Machine Learning into optimization routines is presented. An approach which combines the benefits of ML, optimization, and meta-model searching is developed and tested on a multi-modal test problem; a modified Rastragin's function. An enhanced Particle Swarm Optimization method was derived from the initial testing. Optimization of a diesel engine was carried out using the modified algorithm demonstrating an improvement of 83% compared with the unmodified PSO algorithm. Additionally, an approach to enhancing the training of ML models by leveraging Virtual Sensing as an alternative to standard multi-layer neural networks is presented. Substantial gains were ...


Development Of Physics Based Machine Learning Algorithms, Rob Jennings Jan 2019

Development Of Physics Based Machine Learning Algorithms, Rob Jennings

Master’s Theses

In this study, a baseball pitch was examined to try to understand its behavior, and make a predictive model of it. A baseball pitch was tested experimentally with a wind tunnel and modeled computationally with COMSOL CFD software. Five input variables (spin rate, sting angle, seam orientation: Y axis, seam orientation: Z axis, and air velocity) were controlled, with force in three axes recorded as outputs. The experimental and computational results were examined and seen to be interdependent for all input variables. Experimental and computational data were both insufficient for predicting system behavior. Experimental data collection would have required an ...


Deep Learning For Human Engineered Systems: Weak Supervision, Interpretability And Knowledge Embedding, Sambuddha Ghosal Jan 2019

Deep Learning For Human Engineered Systems: Weak Supervision, Interpretability And Knowledge Embedding, Sambuddha Ghosal

Graduate Theses and Dissertations

Pattern recognition has its origins in engineering while machine learning developed from computer science. Today, artificial intelligence (AI) is a booming field with many practical applications and active research topics that deals with both pattern recognition and machine learning. We now use software and applications to automate routine labor, understand speech (using Natural Language Processing) or images (extracting hierarchical features and patterns for object detection and pattern recognition), make diagnoses in medicine, even intricate surgical procedures and support basic scientific research.

This thesis deals with exploring the application of a specific branch of AI, or a specific tool, Deep Learning ...


Automated Approaches For The Construction Of Image Based Phase Diagrams, Badrinath Balasubramaniam Jan 2019

Automated Approaches For The Construction Of Image Based Phase Diagrams, Badrinath Balasubramaniam

Graduate Theses and Dissertations

In the field of materials science, phase diagram construction is often a laborious process because of the time taken for a human to sift through a large number of images. To mitigate this, machine learning approaches have been used by researchers to automate the construction of these phase diagrams using both supervised and unsupervised learning. In this dissertation, I have outlined a step-wise lego-like approach using both unsupervised learning and image processing approaches to automate the construction of image based phase diagrams and have illustrated that with the construction of three polymer phase diagrams.