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A Multimodal Neuroimaging Approach For Classification And Prediction Of Alzheimer's Disease Using Machine Learning, Parisa Forouzannezhad
A Multimodal Neuroimaging Approach For Classification And Prediction Of Alzheimer's Disease Using Machine Learning, Parisa Forouzannezhad
FIU Electronic Theses and Dissertations
Alzheimer’s disease (AD) is one of the most common neurodegenerative disorders among the elderly population. It is progressive, irreversible in nature, and is considered the main cause of dementia. AD has become a world health problem affecting developed and developing nations alike, with the number of diagnosed AD patients increasing rather dramatically as both the life span of humans and the earth’s population continue to increase. Therefore, AD diagnosis in its earliest manifestations, preferably at the presymptomatic stage is critical for the timely planning of treatment and therapeutic interventions. We introduce new machine learning algorithms to detect and predict Alzheimer’s …
A Comprehensive Security Framework For Securing Sensors In Smart Devices And Applications, Amit Kumar Sikder
A Comprehensive Security Framework For Securing Sensors In Smart Devices And Applications, Amit Kumar Sikder
FIU Electronic Theses and Dissertations
This doctoral dissertation introduces novel security frameworks to detect sensor-based threats on smart devices and applications in smart settings such as smart home, smart office, etc. First, we present a formal taxonomy and in-depth impact analysis of existing sensor-based threats to smart devices and applications based on attack characteristics, targeted components, and capabilities. Then, we design a novel context-aware intrusion detection system, 6thSense, to detect sensor-based threats in standalone smart devices (e.g., smartphone, smart watch, etc.). 6thSense considers user activity-sensor co-dependence in standalone smart devices to learn the ongoing user activity contexts and builds a context-aware model to distinguish malicious …