Browsing OU - Dissertations by Author "Radhakrishnan, Sridhar"
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Adaptive and Restorative Capacity Planning for Complex Infrastructure Networks: Optimization Algorithms and Applications
Morshedlou (tajik), Nazanin (2018)This research focuses on planning and scheduling of adaptive and restorative capacity enhancement efforts provided by complex infrastructure network in the aftermath of disruptive events. To maximize the adaptive capacity, ... -
Application of deep learning to optimize computer-aided-detection and diagnosis of medical images
Maryada, Sai Kiran Reddy (2023-12-15)The field of medical imaging informatics has experienced significant advancements with the integration of artificial intelligence (AI), especially in tasks like detecting abnormalities in retinal fundus images. This ... -
Application of the Forward Sensitivity Method to Data Assimilation of the Lagrangian Tracer Dynamics
Jabrzemski, Rafal (2014-05)The analysis of the dynamics of a tracer/drifter/buoy floating on the free surface of the water waves in the open ocean whose motion is described by the shallow water model equations is of great interest in Lagrangian data ... -
Causal failures and cost-effective edge augmentation in networks
Zhang, Zuyuan (2023-08-04)Node failures have a terrible effect on the connectivity of the network. In traditional models, the failures of nodes affect their neighbors and may further trigger the failures of their neighbors, and so on. However, it ... -
Coastal vulnerability: Impact of port disruptions and the economic impacts of tropical cyclones
Wendler Bosco, Vera (2020-12)Coastal counties in the United States account for less than 10% of the nation’s land mass. Yet, approximately 40% of the country’s population, or over 127 million people, live in these areas. The population density of ... -
Combinatorial algorithms in the approximate computing paradigm
Narasimhan, Aditya (2023-08-04)Data-intensive computing has led to the emergence of data centers with massive processor counts and main memory sizes. However, the demand for shared resources has surpassed their capacity, resulting in increased costs and ... -
Compressing and Performing Algorithms on Massively Large Networks
Nelson, Michael (2019-12-13)Networks are represented as a set of nodes (vertices) and the arcs (links) connecting them. Such networks can model various real-world structures such as social networks (e.g., Facebook), information networks (e.g., citation ... -
Compression techniques for extreme-scale graphs and matrices: sequential and parallel algorithms
Gopal Krishna, Sudhindra (2023-08-04)A graph G = (V, E) is an ordered tuple where V is a non-empty set of elements called vertices (nodes), and E is a set of an unordered pair of elements called links (edges), and a time-evolving graph is a change in the ... -
The Context-Aware Learning Model
Suh, Joohee (2017-12)The ultimate goal of this research is to build a novel, generalized, arbitrary-depth, neural controller that performs reward- and experience-based neuromodulatory learning, which is online, bootstrapping, interactive, ... -
Data gathering techniques on wireless sensor networks
Mohanoor, Aravind (2008)The nearly exponential growth of the performance/price and performance/size ratios of computers has given rise to the development of inexpensive, miniaturized systems with wireless and sensing capabilities. Such wireless ... -
Design, Implementation and Evaluation of an In-House Controller for Software Defined Networking with Applications
Xu, Yiming (2017-12-15)Over the past several decades, there has been a dramatic improvement in net- working technologies. Network devices and protocols are becoming more powerful and complex. The vertical structure of the network protocol layers ... -
Design, Implementation, and Evaluation of Join and Split Strategy for Transmission control protocol running on Software Defined Networks
Guo, Wei (2017-12-15)Software Defined Networks (SDN)-enabled switches of today can be empowered to intelligently forward as well as elastically steer the network traffic. In this work, we focus on developing a SDN-based framework to provide ... -
Developing and Applying Hybrid Deep Learning Models for Computer-Aided Diagnosis of Medical Image Data
Mudduluru, Sanjana (2023)The dissertation discusses three methods to address the challenges of applying deep learning models to medical imaging. The first method involves the development of a new joint deep learning model, J-Net, to achieve lesion ... -
DEVELOPMENT OF HIGH-THROUGHPUT EXPERIMENTAL AND COMPUTATIONAL TECHNOLOGIES FOR ANALYZING MICROBIAL FUNCTIONS AND INTERACTIONS IN ENVIRONMENTAL METAGENOMES
Shi, Zhou (2017-05-12)Microorganisms are ubiquitous on earth, and they interact each other to form communities, which play unique and integral roles in various biochemical processes and functions that are of critical importance in global ... -
ENERGY-EFFICIENT PROTOCOL DESIGN AND ANALYSIS FOR WIRELESS SENSOR NETWORKS
ZHENG, TAO (2011)Wireless sensor networks are an emerging technology which has the promise of revolutionizing the way of collecting, processing and disseminating information. Due to the small sizes of sensor nodes, resources like battery ... -
Essays on Networks in Auctions
Press, Robert (2021-05-14)My dissertation chapters study the effects networks play in an auction setting. My first chapter explores how subcontracting creates affiliation between firm's costs in an auction setting. It first offers a theoretical ... -
Extended Observation Particle Filter with SVD Template Generation Implemented for GPU
Williams, Jonathan (2018-12)This work presents a novel template updating strategy based on singular value decomposition (SVD) together with an expansion and extension of previous work combining observations across temporally adjacent frames to implement ... -
Fair Resource Allocation in Macroscopic Evacuation Planning Using Mathematical Programming: Modeling and Optimization
Bin Obaid, Hamoud (2020)Evacuation is essential in the case of natural and manmade disasters such as hurricanes, nuclear disasters, fire accidents, and terrorism epidemics. Random evacuation plans can increase risks and incur more losses. Hence, ... -
Feedback and Requirement Biasing for Enhancing Robustness of Scheduling Algorithms for Distributed System Processing
Grounds, Nicolas (2018-12)Scheduling tasks in a distributed system (e.g., cloud computing) in order to optimize an objective such as minimizing deadline misses has been a topic of research for decades. Such a problem is proven NP Complete even ... -
Forecast Uncertainty Quantification using Monte Carlo, Polynomial Chaos Expansion and Unscented Transformation Methods
Hu, Junjun (2015-12-18)In the context of prediction science, the sources of uncertainty can be from the uncertainties of the experiments, modeling, model inputs, numerical analysis, etc. This study concentrates on quantifying the forecast ...