Physical Sciences and Mathematics Commons^™

Reducing Instrumentation Barriers Of Diffuse Correlation Spectroscopy For Low-Cost Deep Tissue Blood Flow Monitoring, Arindam Biswas

USF Tampa Graduate Theses and Dissertations

Cerebral blood flow (CBF) is a good indicator of brain health as blood carries necessary nutrients, oxygen, and metabolic byproducts. Quantitative blood flow information can be used in several clinical and therapeutic applications such as stroke detection, measuring autoregulation, evaluating brain injury, or determining neuronal activity. Over the past few decades, light-based deep tissue hemodynamic detection modalities have become popular for non-invasive CBF measurements. In particular, noninvasive Diffuse Correlation Spectroscopy (DCS), has become a tool of choice for research and clinical applications due to its depth sensitivity (>1 cm), portability, validity against other technologies such as Magnetic Resonance Imaging …

Frequency Domain Diffuse Optics Spectroscopies For Quantitative Measurement Of Tissue Optical Properties, Sadhu Moka

USF Tampa Graduate Theses and Dissertations

Tissue oxygen saturation, blood flow and blood volume are physiological bio-markers of tissue health. Diffuse Optical Spectroscopy(DOS) and Diffuse Correlation Spectroscopy (DCS) are two complementary approaches to measure tissue oxygen saturation and blood flow respectively. Quantitative Diffuse Optical Spectroscopy (DOS) uses multi-spectral intensities of near-infrared light that have been modulated at RF frequencies to estimate static tissue optical properties and hence concentrations of oxygenated and de-oxygenated hemoglobin. Diffuse Correlation Spectroscopy estimates tissue dynamics - i.e., blood flow, by measuring temporal intensity auto-correlation function of backscattered light diffusing through the tissue. Conventionally, DCS instruments use coherent light sources with constant intensity. …

Development Of An Automated Platform For Sensing And Differentiating Vapor-Phase Btex Constituents, Jonathan Samuelson

USF Tampa Graduate Theses and Dissertations

Light aromatic hydrocarbons are an inevitable byproduct of fossil fuel extraction, refinement, distribution, and use. The four lightest and most prevalent of these are benzene, toluene, ethylbenzene, and xylene, which are known collectively as BTEX. In spite of their chemical similarity these species have markedly different effects on human health and substantially different concentrations are permitted by OSHA in workplaces and by the EPA in ambient air and groundwater. Real-time detection, identification, and quantification of these species is therefore of great importance wherever they see industrial use.This work represents the continuation and advancement of a line of research in which …

Accelerating Multiparametric Mri For Adaptive Radiotherapy, Shraddha Pandey

USF Tampa Graduate Theses and Dissertations

MR guided Radiotherapy (MRgRT) marks an important paradigm shift in the field of radiotherapy. Superior tissue contrast of MRI offers better visualization of the abnormal lesions, as a result precise radiation dose delivery is possible. In case of online treatment planning, MRgRT offers better control of intratumoral motion and quick adaptation to changes in the gross tumor volume. Nonetheless, the MRgRT process flow does suffer from some challenges that limit its clinical usability. The primary aspects of MRgRT workflow are MRI acquisition, tumor delineation, dose map prediction and administering treatment. It is estimated that the acquisition of MRI takes around …

Explainable And Cooperative Autonomy Across Networks Of Distributed Systems, Peter Joseph Jorgensen

USF Tampa Graduate Theses and Dissertations

Large networks of complex systems-of-systems are commonplace and evermore present in both mundane and extraordinary facets of human existence. From the exponential growth of connectivity via the internet and other information networks, to the miniaturization of computers and sensors, to cross-domain sensor and communication networks, these networks of distributed systems-of-systems (NDSS) present incredible benefits and challenges. Autonomy is perhaps the most important and most difficult to achieve enabling technology for efficient performance of the NDSS. Giving each individual agent in a network the ability to manage its internal state in dynamic operating environments and in pursuit of multiple complex and …

Data-Driven Design And Analysis Of Next Generation Mobile Networks For Anomaly Detection And Signal Classification With Fast, Robust And Light Machine Learning, Muhammed Furkan Küçük

USF Tampa Graduate Theses and Dissertations

This research focuses on machine (and deep) learning applications (including clustering,anomaly detection and signal classification) for self-organizing and next generation mobile networks in wireless communications. Specifically, this dissertation document will address the three different topics.

First, in the study titled “Performance analysis of neural network topologies and hyperparameters for deep clustering”, we explore the relationship between the clustering performance and network complexity. Deep learning found its initial footing in supervised applications such as image and voice recognition successes of which were followed by deep generative models across similar domains. In recent years, researchers have proposed creative learning representations to utilize …

Finding Signal In The Noise: High-Fidelity, Quantitative, Optical Blood Perfusion Imaging With Interference, Abdul Mohaimen Safi

USF Tampa Graduate Theses and Dissertations

For label-free, non-invasive, wide field-of-view (FOV) imaging/monitoring of blood flow, speckle-based approaches are gaining popularity. However, to obtain quantitative flow information, speckle techniques rely on the multi-exposure scheme which requires complex, bulky, and expensive instrumentation, limiting its application to preclinical studies. This dissertation directly addresses these issues. In the first part of this dissertation, we report a novel single shot synthetic multi-exposure speckle imaging (syMESI) method to synthetically produce multi-exposure images from one short single exposure speckle image using spatial binning/averaging. We demonstrate that syMESI can reimagine conventional hardware based MESI, with low-cost single exposure laser speckle imaging (LSCI) instrumentation. …

Soft Magnetic Composite Substrates For Rf/Microwave Applications, Poonam Lathiya

USF Tampa Graduate Theses and Dissertations

Novel soft magnetic ferrite materials will play a crucial role in next-generation over one trillion sensors (also known as “trillion sensor economy) related to 5G communications and internet of things, as these materials can achieve improved wireless power and signal transfer efficiency with high operation frequency. In this work, Ni-Cu-Zn and Ni-Co-Zn ferrites with high permeability, high permittivity, and low magnetic and dielectric losses were prepared for RF and microwave device applications. Frequency dispersion of RF complex permeability of Ni-Cu-Zn ferrites prepared under different applied hydraulic pressures and durations have been thoroughly investigated. The Ni0.35Cu0.19Zn0.46Fe2O4 ferrites were prepared by conventional …

Fiber-Based Electrical Energy Storage And Harvesting Devices For Wearable Electronics, Tareq Kareri

USF Tampa Graduate Theses and Dissertations

Over the past few years, smart textiles and wearable technologies have received tremendous attention due to their functionalities and characteristics, which could be used in a variety of ways in healthcare, sports/leisure, fashion, military, personal protective, and energy applications. These technologies depend on self-power systems, which require energy sources (e.g., batteries, supercapacitors, and solar cells) to power their projected functionalities in the future. Therefore, fabricating energy harvesting cells (i.e., solar cells) and energy storage cells (i.e., batteries and supercapacitors) in the form of fibers are promising solutions for powering wearable electronics due to their unique features such as flexibility and …