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Full-Text Articles in Computer Engineering

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel Jan 2022

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel

Theses and Dissertations

This thesis presents a learning from demonstration framework that enables a robot to learn and perform creative motions from human demonstrations in real-time. In order to satisfy all of the functional requirements for the framework, the developed technique is comprised of two modular components, which integrate together to provide the desired functionality. The first component, called Dancing from Demonstration (DfD), is a kinesthetic learning from demonstration technique. This technique is capable of playing back newly learned motions in real-time, as well as combining multiple learned motions together in a configurable way, either to reduce trajectory error or to generate entirely …


Machine Learning (Ml) - Assisted Tools For Enhancing Security And Privacy Of Edge Devices, Santosh Kumar Nukavarapu Jan 2022

Machine Learning (Ml) - Assisted Tools For Enhancing Security And Privacy Of Edge Devices, Santosh Kumar Nukavarapu

Theses and Dissertations

The rapid growth of edge-based IoT devices, their use cases, and autonomous communication has created new challenges with privacy and security. Side-channel attacks are one of the examples of security and privacy vulnerabilities that can cause inference at Internet-Service Provider (ISP) and local Wi-Fi networks. Such an attack would leak user’s sensitive information such as home occupancy, medical activity, and daily routines. Another example is that these devices have weak authentication and low encryption standards, making them an easy target for malware-based attacks such as denial of service or launching other network attacks using these infected devices. This thesis dissertation …


Data Science Methods For Standardization, Safety, And Quality Assurance In Radiation Oncology, Khajamoinuddin Syed Jan 2020

Data Science Methods For Standardization, Safety, And Quality Assurance In Radiation Oncology, Khajamoinuddin Syed

Theses and Dissertations

Radiation oncology is the field of medicine that deals with treating cancer patients through ionizing radiation. The clinical modality or technique used to treat the cancer patients in the radiation oncology domain is referred to as radiation therapy. Radiation therapy aims to deliver precisely measured dose irradiation to a defined tumor volume (target) with as minimal damage as possible to surrounding healthy tissue (organs-at-risk), resulting in eradication of the tumor, high quality of life, and prolongation of survival. A typical radiotherapy process requires the use of different clinical systems at various stages of the workflow. The data generated in these …


Internal Medicine, Keroles Hakem, Robert Trachy, Khanh Tran Jan 2017

Internal Medicine, Keroles Hakem, Robert Trachy, Khanh Tran

Capstone Design Expo Posters

Our objective was to develop a model to predict the length of stay of patients using data from MCV. We conducted our analysis using a dataset of over 130,000 patients described by 66 features. The features contained clinical characteristics (e.g. diagnosis), facility characteristics (e.g. bed type), and socioeconomic characteristics (e.g. insurance type). Our study was focused on patients that stayed in the hospital. To cope with data imperfections, such as missing data, we applied data cleaning methods. Using learned domain knowledge, we identified 9 features to build our predictive models: admit source, primary insurance, discharge disposition, admit unit, iso result, …


Improving Understandability And Uncertainty Modeling Of Data Using Fuzzy Logic Systems, Dumidu S. Wijayasekara Jan 2016

Improving Understandability And Uncertainty Modeling Of Data Using Fuzzy Logic Systems, Dumidu S. Wijayasekara

Theses and Dissertations

The need for automation, optimality and efficiency has made modern day control and monitoring systems extremely complex and data abundant. However, the complexity of the systems and the abundance of raw data has reduced the understandability and interpretability of data which results in a reduced state awareness of the system. Furthermore, different levels of uncertainty introduced by sensors and actuators make interpreting and accurately manipulating systems difficult. Classical mathematical methods lack the capability to capture human knowledge and increase understandability while modeling such uncertainty.

Fuzzy Logic has been shown to alleviate both these problems by introducing logic based on vague …