Physical Sciences and Mathematics Commons^™

Image Encryption And Stegenography Based On Computational Single Pixel Imaging, Hossein Ghanbari Ghalehjoughi

Theses and Dissertations

Multiple layers of information security are introduced based on computational ghost imaging (CGI). We show, in the first step, that it is possible to design a very reliable image encryption scheme using 3D computational ghost imaging with two single-pixel detectors sending data through two channels. Through the Normalized Root Mean Square scale, it is then shown that a further level of security can be achieved by merging data-carrying channels into one and using a coded order for their placement in the sequence of bucket data carried by the single channel. Yet another layer of security is introduced through hiding the …

Cloud Based Iot Architecture, Nathan Roehl

Theses and Dissertations

The Internet of Things (IoT) and cloud computing have grown in popularity over the past decade as the internet becomes faster and more ubiquitous. Cloud platforms are well suited to handle IoT systems as they are accessible and resilient, and they provide a scalable solution to store and analyze large amounts of IoT data. IoT applications are complex software systems and software developers need to have a thorough understanding of the capabilities, limitations, architecture, and design patterns of cloud platforms and cloud-based IoT tools to build an efficient, maintainable, and customizable IoT application. As the IoT landscape is constantly changing, …

An Implementation Of Fully Convolutional Network For Surface Mesh Segmentation, Taiyu Zhang

Theses and Dissertations

This thesis presents an implementation of a 3-Dimensional triangular surface mesh segmentation architecture named Shape Fully Convolutional Network, which is proposed by Pengyu Wang and Yuan Gan in 2018. They designed a deep neural network that has a similar architecture as the Fully Convolutional Network, which provides a good segmentation result for 2D images, on 3D triangular surface meshes. In their implementation, 3D surface meshes are represented as graph structures to feed the network. There are three main barriers when applying the Fully Convolutional Network to graph-based data structures.

• First, the pooling operation is much harder to apply to …

Scatter Reduction By Exploiting Behaviour Of Convolutional Neural Networks In Frequency Domain, Carlos Ivan Jerez Gonzalez

Theses and Dissertations

In X-ray imaging, scattered radiation can produce a number of artifacts that greatly

undermine the image quality. There are hardware solutions, such as anti-scatter grids.

However, they are costly. A software-based solution is a better option because it is

cheaper and can achieve a higher scatter reduction. Most of the current software-based

approaches are model-based. The main issues with them are the lack of flexibility, expressivity, and the requirement of a model. In consideration of this, we decided to apply

Convolutional Neural Networks (CNNs), since they do not have any of the previously

mentioned issues.

In our approach we split …

A Pedagogy Of Techno-Social Relationality: Ethics And Digital Multimodality In The Composition Classroom, Kristin M. Ravel

Theses and Dissertations

I bring together the relational ethics of feminist critical theory with approaches of multimodal rhetoric to examine the ethical implications of composing on social media platforms. Most social media platforms are designed to value consumerism, efficiency, quantity of web traffic, and constant synchronous response over concerns of responsible and critical communication. I propose a rhetorical approach of techno-social relationality (TSR) as an intervention against such corporate-minded design. Through this approach, I argue that civil engagement is not limited to people’s social responsibilities but rather is entwined in complex, material-technical contexts. By considering the responsibility of our machines as much as …

A Minimal Time Solution To The Firing Squad Synchronization Problem With Von Neumann Neighborhood Of Extent 2, Kathryn Boddie

Theses and Dissertations

Cellular automata provide a simple environment in which to study global behaviors. One example of a problem that utilizes cellular automata is the Firing Squad Synchronization Problem, first proposed in 1957. This paper provides an overview of the standard Firing Squad Synchronization Problem and a commonly used technique in solving it. This paper also provides a statement of a new extension of the Standard Firing Squad Synchronization Problem to a different neighborhood definition - a Von Neumann neighborhood of extent 2. An 8 state 651 rule minimal time solution to the extended problem is described, presented and proven, along with …

Model Augmented Deep Neural Networks For Medical Image Reconstruction Problems, Hongquan Zuo

Theses and Dissertations

Solving an ill-posed inverse problem is difficult because it doesn't have a unique solution. In practice, for some important inverse problems, the conventional methods, e.g. ordinary least squares and iterative methods, cannot provide a good estimate. For example, for single image super-resolution and CT reconstruction, the results of these conventional methods cannot satisfy the requirements of these applications. While having more computational resources and high-quality data, researchers try to use machine-learning-based methods, especially deep learning to solve these ill-posed problems. In this dissertation, a model augmented recursive neural network is proposed as a general inverse problem method to solve these …

Use Of Text Data In Identifying And Prioritizing Potential Drug Repositioning Candidates, Majid Rastegar-Mojarad

Theses and Dissertations

New drug development costs between 500 million and 2 billion dollars and takes 10-15 years, with a success rate of less than 10%. Drug repurposing (defined as discovering new indications for existing drugs) could play a significant role in drug development, especially considering the declining success rates of developing novel drugs. In the period 2007-2009, drug repurposing led to the launching of 30-40% of new drugs. Typically, new indications for existing medications are identified by accident. However, new technologies and a large number of available resources enable the development of systematic approaches to identify and validate drug-repurposing candidates with significantly …

Predicting Hospital Length Of Stay In Intensive Care Unit, Namita Singh

Theses and Dissertations

In this thesis, we investigate the performance of a series of classification methods for the

Prediction of the hospital Length of Stay (LoS) in Intensive Care Unit (ICU). Predicting

LOS for an inpatient in an hospital is a challenging task but is essential for the operational

success of a hospital. Since hospitals are faced with severely limited resources including

beds to hold admitted patients, prediction of LoS will assist the hospital staff for better

planning and management of hospital resources. The goal of this project is to create a

machine learning model that predicts the length-of stay for each patient …

Machine Intelligence For Advanced Medical Data Analysis: Manifold Learning Approach, Fereshteh S Bashiri

Theses and Dissertations

In the current work, linear and non-linear manifold learning techniques, specifically Principle Component Analysis (PCA) and Laplacian Eigenmaps, are studied in detail. Their applications in medical image and shape analysis are investigated.

In the first contribution, a manifold learning-based multi-modal image registration technique is developed, which results in a unified intensity system through intensity transformation between the reference and sensed images. The transformation eliminates intensity variations in multi-modal medical scans and hence facilitates employing well-studied mono-modal registration techniques. The method can be used for registering multi-modal images with full and partial data.

Next, a manifold learning-based scale invariant global shape …

Cad-Based Porous Scaffold Design Of Intervertebral Discs In Tissue Engineering, Ye Guo

Theses and Dissertations

With the development and maturity of three-dimensional (3D) printing technology over the past decade, 3D printing has been widely investigated and applied in the field of tissue engineering to repair damaged tissues or organs, such as muscles, skin, and bones, Although a number of automated fabrication methods have been developed to create superior bio-scaffolds with specific surface properties and porosity, the major challenges still focus on how to fabricate 3D natural biodegradable scaffolds that have tailor properties such as intricate architecture, porosity, and interconnectivity in order to provide the needed structural integrity, strength, transport, and ideal microenvironment for cell- and …

Three Essays On Individuals’ Vulnerability To Security Attacks In Online Social Networks: Factors And Behaviors, Neshat Beheshti

Theses and Dissertations

With increasing reliance on the Internet, the use of online social networks (OSNs) for communication has grown rapidly. OSN platforms are used to share information and communicate with friends and family. However, these platforms can pose serious security threats to users. In spite of the extent of such security threats and resulting damages, little is known about factors associated with individuals’ vulnerability to online security attacks. We address this gap in the following three essays.

Essay 1 draws on a synthesis of the epidemic theory in infectious disease epidemiology with the social capital theory to conceptualize factors that contribute to …

Culture And Code: The Evolution Of Digital Architecture And The Formation Of Networked Publics, Geoffrey Gimse

Theses and Dissertations

Culture and Code traces the construction of the modern idea of the Internet and offers a potential glimpse of how that idea may change in the near future. Developed through a theoretical framework that links Sheila Jasanoff and Sang-Hyun Kim’s theory of the sociotechnical imaginary to broader theories on publics and counterpublics, Culture and Code offers a way to reframe the evolution of Internet technology and its culture as an enmeshed part of larger socio-political shifts within society. In traveling the history of the modern Internet as detailed in its technical documentation, legal documents, user created content, and popular media …

Deep Learning Applications In Medical Image And Shape Analysis, Jingtao Yang

Theses and Dissertations

Deep learning is one of the most rapidly growing fields in computer and data science in the past few years. It has been widely used for feature extraction and recognition in various applications. The training process as a black-box utilizes deep neural networks, whose parameters are adjusted by minimizing the difference between the predicted feedback and labeled data (so-called training dataset). The trained model is then applied to unknown inputs to predict the results that mimic human's decision-making. This technology has found tremendous success in many fields involving data analysis such as images, shapes, texts, audio and video signals and …

The Assessment Of Technology Adoption Interventions And Outcome Achievement Related To The Use Of A Clinical Research Data Warehouse, Katie A. Mccarthy

Theses and Dissertations

Introduction: While funding for research has declined since 2004, the need for rapid, innovative, and lifesaving clinical and translational research has never been greater due to the rise in chronic health conditions, which have resulted in lower life expectancy and higher rates of mortality and adverse outcomes. Finding effective diagnostic and treatment methods to address the complex challenges in individual and population health will require a team science approach, creating the need for multidisciplinary collaboration among practitioners and researchers.

To address this need, the National Institutes of Health (NIH) created the Clinical and Translational Science Awards (CTSA) program. The CTSA …

Predicting Hospital Length Of Stay In Intensive Care Unit, Namita Singh

Theses and Dissertations

In this thesis, we investigate the performance of a series of classification methods for the

Prediction of the hospital Length of Stay (LoS) in Intensive Care Unit (ICU). Predicting

LOS for an inpatient in an hospital is a challenging task but is essential for the operational

success of a hospital. Since hospitals are faced with severely limited resources including

beds to hold admitted patients, prediction of LoS will assist the hospital staff for better

planning and management of hospital resources. The goal of this project is to create a

machine learning model that predicts the length-of stay for each patient …

Deep Learning Applications In Medical Image And Shape Analysis, Jingtao Yang

Theses and Dissertations

Deep learning is one of the most rapidly growing fields in computer and data science in the past few years. It has been widely used for feature extraction and recognition in various applications. The training process as a black-box utilizes deep neural networks, whose parameters are adjusted by minimizing the difference between the predicted feedback and labeled data (so-called training dataset). The trained model is then applied to unknown inputs to predict the results that mimic human's decision-making. This technology has found tremendous success in many fields involving data analysis such as images, shapes, texts, audio and video signals and …

Optical Fiber Communication With Vortex Modes, Du'a Al-Zaleq

Theses and Dissertations

Internet data traffic’s capacity is rapidly reaching limits imposed by optical fiber nonlinearities [5]. Optical vortices appear in high order fiber optical mode. In this thesis, we consider multimode fibers (MMFs) that are capable of transmitting a few vortex modes. Certain types of fibers have a spatial dimension leads to space-division-multiplexing (SDM), where information is transmitted with cores of multicore fibers (MCFs) or mode-division-multiplexing (MDM), where information is transmitted via different modes of multimode fibers (MMFs). SDM by employing few-mode fibers in optical networks is expected to efficiently enhance the capacity and overcome the capacity crunch owing to fast increasing …