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Articles 1 - 4 of 4
Full-Text Articles in Engineering
Quantum State Estimation And Tracking For Superconducting Processors Using Machine Learning, Shiva Lotfallahzadeh Barzili
Quantum State Estimation And Tracking For Superconducting Processors Using Machine Learning, Shiva Lotfallahzadeh Barzili
Computational and Data Sciences (PhD) Dissertations
Quantum technology has been rapidly growing; in particular, the experiments that have been performed with superconducting qubits and circuit QED have allowed us to explore the light-matter interaction at its most fundamental level. The study of coherent dynamics between two-level systems and resonator modes can provide insight into fundamental aspects of quantum physics, such as how the state of a system evolves while being continuously observed. To study such an evolving quantum system, experimenters need to verify the accuracy of state preparation and control since quantum systems are very fragile and sensitive to environmental disturbance. In this thesis, I look …
Machine-Learning-Based Approach To Decoding Physiological And Neural Signals, Elnaz Lashgari
Machine-Learning-Based Approach To Decoding Physiological And Neural Signals, Elnaz Lashgari
Computational and Data Sciences (PhD) Dissertations
In recent years, machine learning algorithms have been developing rapidly, becoming increasingly powerful tools in decoding physiological and neural signals. The aim of this dissertation is to develop computational tools, and especially machine learning techniques, to identify the most effective methods for feature extraction and classification of these signals. This is particularly challenging due to the highly non-linear, non-stationery, and artifact- and noise-prone nature of these signals.
Among basic human-control tasks, reaching and grasping are ubiquitous in everyday life. I investigated different linear and non-linear dimensionality reduction techniques for feature extraction and classification of electromyography (EMG) during a reach-grasp-lift task. …
Contributing To Engineering Colleges Students' Development Through Out-Of-Class Involvement: A Survey Of Chinese Private Colleges' Engineering Students, Wanlu Li
Education (PhD) Dissertations
The purpose of this study was to investigate the primary characteristics of engineering college students’ involvement in out-of-class activities (OA) at one private college in China through the use of the translated and culturally adapted Chinese version of the Postsecondary Student Engagement Survey (PosSES 2.1). This study provides the statistical analyses of the survey data completed by 283 senior engineering students on their perceptions about their levels of involvement related to positive/negative outcomes students perceive and affective engagement. Data results showed all levels of involvement have a significant influence on positive outcomes. Besides, active involvement degree, hours, and types of …
Optimal Analytical Methods For High Accuracy Cardiac Disease Classification And Treatment Based On Ecg Data, Jianwei Zheng
Optimal Analytical Methods For High Accuracy Cardiac Disease Classification And Treatment Based On Ecg Data, Jianwei Zheng
Computational and Data Sciences (PhD) Dissertations
This work constitutes six projects. In the first project, a newly inaugurated research database for 12-lead electrocardiogram signals was created under the auspices of Chapman University and Shaoxing People's Hospital (Shaoxing Hospital Zhejiang University School of Medicine). This database aims to enable the scientific community in conducting new studies on arrhythmia and other cardiovascular conditions. In the second project, we created a new 12-lead ECG database under the auspices of Chapman University and Ningbo First Hospital of Zhejiang University that aims to provide high quality data enabling detection of the distinctions between idiopathic ventricular arrhythmia from right ventricular outflow tract …