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Filtering by: Creator Green, Dale Resource Type Dissertation Rights Statement In Copyright - Non-Commercial Use Permitted

Restoring Ponderosa Pine: Understanding Individual Tree Defenses, Disturbance Responses, and Resilience

Creator:

Johnson, Christal

Abstract:

The aim of this research was to provide forest managers and researchers with a better understanding of individual tree defenses and tree responses to disturbances, within a Collaborative Forest Landscape Restoration Program area. Forest restoration often aims to increase stand-level resistance to uncharacteristic changes, and stand-level resistance begins with tree-level...

Resource Type:

Dissertation

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also contributing to increased intensity and/or frequency of disturbances (Dale et al., 2001; Earles
Machine Learning for Precision Medicine: Application to Cancer Chemotherapy Response Prediction and Wound Healing Status Assessment

Creator:

Wei, Qi

Abstract:

Ph.D. candidate Qi Wei's thesis consists of two projects: Chemotherapy Project: a study based on the research paper "Predicting chemotherapy response of various cancer types using a variational auto-encoder approach" submitted to the bioRxiv preprint archive and accepted by the BMC bioinformatics; and Wound Monitor Project: implementing and assessing analytics...

Resource Type:

Dissertation

Full Text:

sarcoma, for three di↵erent machine learning models (SVM: Support Vector Ma- chine (Green, Sec. 2.3.4.2