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Full-Text Articles in Engineering
Advanced Deep Learning Methodologies For Deepfake Detection, Aminollah Khormali
Advanced Deep Learning Methodologies For Deepfake Detection, Aminollah Khormali
Electronic Theses and Dissertations, 2020-
The recent advances in the field of Artificial Intelligence (AI), particularly Generative Adversarial Networks (GANs) and an abundance of training samples along with robust computational resources have significantly propelled the field of AI-generated fake information in all kinds, e.g., deepfakes. Deepfakes are among the most sinister types of misinformation, posing large-scale and severe security and privacy risks targeting critical governmental institutions and ordinary people across the world. The fact that deepfakes are AI-generated digital content and not actual events captured by a camera implies that they still can be detected using advanced AI models. Although the deepfake detection task has …
Directional Spectral Solar Energy For Building Performance: From Simulation To Cyber-Physical Prototype, Joseph Del Rocco
Directional Spectral Solar Energy For Building Performance: From Simulation To Cyber-Physical Prototype, Joseph Del Rocco
Electronic Theses and Dissertations, 2020-
The original research and development in this dissertation contributes to the field of building performance by actively harnessing a wider spectrum of directional solar radiation for use in buildings. Solar radiation (energy) is often grouped by wavelength measurement into the spectra ultraviolet (UV), visible (light), and short and long-wave infrared (heat) on the electromagnetic spectrum. While some of this energy is directly absorbed or deflected by our atmosphere, most of it passes through, scatters about, and collides with our planet. Modern building performance simulations, tools, and control systems often oversimplify this energy into scalar values for light and heat, when …
Secure And Trustworthy Hardware And Machine Learning Systems For Internet Of Things, Shayan Taheri
Secure And Trustworthy Hardware And Machine Learning Systems For Internet Of Things, Shayan Taheri
Electronic Theses and Dissertations, 2020-
The advancements on the Internet have enabled connecting more devices into this technology every day. This great connectivity has led to the introduction of the internet of things (IoTs) that is a great bed for engagement of all new technologies for computing devices and systems. Nowadays, the IoT devices and systems have applications in many sensitive areas including military systems. These challenges target hardware and software elements of IoT devices and systems. Integration of hardware and software elements leads to hardware systems and software systems in the IoT platforms, respectively. A recent trend for the hardware systems is making them …
Fpga-Augmented Secure Crash-Consistent Non-Volatile Memory, Yu Zou
Fpga-Augmented Secure Crash-Consistent Non-Volatile Memory, Yu Zou
Electronic Theses and Dissertations, 2020-
Emerging byte-addressable Non-Volatile Memory (NVM) technology, although promising superior memory density and ultra-low energy consumption, poses unique challenges to achieving persistent data privacy and computing security, both of which are critically important to the embedded and IoT applications. Specifically, to successfully restore NVMs to their working states after unexpected system crashes or power failure, maintaining and recovering all the necessary security-related metadata can severely increase memory traffic, degrade runtime performance, exacerbate write endurance problem, and demand costly hardware changes to off-the-shelf processors. In this thesis, we summarize and expand upon two of our innovative works, ARES and HERMES, to design …
Novel Computational Approaches For Multidimensional Brain Image Analysis, Harish Raviprakash
Novel Computational Approaches For Multidimensional Brain Image Analysis, Harish Raviprakash
Electronic Theses and Dissertations, 2020-
The overall goal of this dissertation is focused on addressing challenging problems in 1D, 2D/3D and 4D neuroimaging by developing novel algorithms that combine signal processing and machine learning techniques. One of these challenging tasks is the accurate localization of the eloquent language cortex in brain resection pre-surgery patients. This is especially important since inaccurate localization can lead to diminshed functionalities and thus, a poor quality of life for the patient. The first part of this dissertation addresses this problem in the case of drug-resistant epileptic patients. We propose a novel machine learning based algorithm to establish an alternate electrical …