Engineering Commons^™

Improving Table Scans For Trie Indexed Databases, Ethan Toney

Theses and Dissertations--Computer Science

We consider a class of problems characterized by the need for a string based identifier that reflect the ontology of the application domain. We present rules for string-based identifier schemas that facilitate fast filtering in databases used for this class of problems. We provide runtime analysis of our schema and experimentally compare it with another solution. We also discuss performance in our solution to a game engine. The string-based identifier schema can be used in addition scenarios such as cloud computing. An identifier schema adds metadata about an element. So the solution hinges on additional memory but as long as …

Contributions To Edge Computing, Vernon K. Bumgardner

Theses and Dissertations--Computer Science

Efforts related to Internet of Things (IoT), Cyber-Physical Systems (CPS), Machine to Machine (M2M) technologies, Industrial Internet, and Smart Cities aim to improve society through the coordination of distributed devices and analysis of resulting data. By the year 2020 there will be an estimated 50 billion network connected devices globally and 43 trillion gigabytes of electronic data. Current practices of moving data directly from end-devices to remote and potentially distant cloud computing services will not be sufficient to manage future device and data growth.

Edge Computing is the migration of computational functionality to sources of data generation. The importance of …

Mammogram And Tomosynthesis Classification Using Convolutional Neural Networks, Xiaofei Zhang

Theses and Dissertations--Computer Science

Mammography is the most widely used method of screening for breast cancer. Traditional mammography produces two-dimensional X-ray images, while advanced tomosynthesis mammography produces reconstructed three-dimensional images. Due to high variability in tumor size and shape, and the low signal-to-noise ratio inherent to mammography, manual classification yields a significant number of false positives, thereby contributing to an unnecessarily large number of biopsies performed to reduce the risk of misdiagnosis. Achieving high diagnostic accuracy requires expertise acquired over many years of experience as a radiologist.

The convolutional neural network (CNN) is a popular deep-learning construct used in image classification. The convolutional process …

3d Body Tracking Using Deep Learning, Qingguo Xu

Theses and Dissertations--Computer Science

This thesis introduces a 3D body tracking system based on neutral networks and 3D geometry, which can robustly estimate body poses and accurate body joints. This system takes RGB-D data as input. Body poses and joints are firstly extracted from color image using deep learning approach. The estimated joints and skeletons are further translated to 3D space by using camera calibration information. This system is running at the rate of 3 4 frames per second. It can be used to any RGB-D sensors, such as Kinect, Intel RealSense [14] or any customized system with color depth calibrated. Comparing to the …

Using Natural Language Processing And Machine Learning Techniques To Characterize Configuration Bug Reports: A Study, Wei Wen

Theses and Dissertations--Computer Science

In this study, a tool is developed that achieves two purposes: (1) given bug reports, it identifies configuration bug reports from non-configuration bug reports; (2) once a bug report is identified to be a configuration bug report, the tool finds out what specific configuration option the bug report is associated.

This study starts with a review of related works that used machine learning tools to solve software bug and bug report related issues. It then discusses the natural language processing and machine learning techniques. Afterwards, the development process of the proposed tool is described in detail, including the motivation, the …

Modeling Faceted Browsing With Category Theory For Reuse And Interoperability, Daniel R. Harris

Theses and Dissertations--Computer Science

Faceted browsing (also called faceted search or faceted navigation) is an exploratory search model where facets assist in the interactive navigation of search results. Facets are attributes that have been assigned to describe resources being explored; a faceted taxonomy is a collection of facets provided by the interface and is often organized as sets, hierarchies, or graphs. Faceted browsing has become ubiquitous with modern digital libraries and online search engines, yet the process is still difficult to abstractly model in a manner that supports the development of interoperable and reusable interfaces. We propose category theory as a theoretical foundation for …

Routing And Security In Mobile Ad Hoc Networks, Baban A. Mahmood

Theses and Dissertations--Computer Science

A Mobile Ad hoc Network (MANET) consists of a set of nodes which can form a network among themselves. MANETs have applications in areas such as military, disaster rescue operations, monitoring animal habitats, etc. where establishing fixed communication infrastructure is not feasible. Routing protocols designed for MANETs can be broadly classified as position-based (geographic), topology-based and hybrid. Geographic routing uses location information of nodes to route messages. Topology-based routing uses network state information for route discovery and maintenance. Hybrid routing protocols use features in both position-based and topology-based approaches. Position-based routing protocols route packets towards the destination using greedy forwarding …

Understanding Home Networks With Lightweight Privacy-Preserving Passive Measurement, Xuzi Zhou

Theses and Dissertations--Computer Science

Homes are involved in a significant fraction of Internet traffic. However, meaningful and comprehensive information on the structure and use of home networks is still hard to obtain. The two main challenges in collecting such information are the lack of measurement infrastructure in the home network environment and individuals’ concerns about information privacy.

To tackle these challenges, the dissertation introduces Home Network Flow Logger (HNFL) to bring lightweight privacy-preserving passive measurement to home networks. The core of HNFL is a Linux kernel module that runs on resource-constrained commodity home routers to collect network traffic data from raw packets. Unlike prior …

The Drag Language, Weixi Ma

Theses and Dissertations--Computer Science

This thesis describes the Drag language. Drag is a general purpose, gradually typed, lexically scoped, and multi-paradigm pro- gramming language. The essence of Drag is to build the abstract syntax trees of the programs directly and interactively. Our work includes the language specification and a prototype program. The language specification focuses on the syntax, the semantic model, and the type system. The prototype consists of an interactive editor and a compiler that targets several plat- forms, among which we focus on the LLVM platform in this thesis.

A Network Path Advising Service, Xiongqi Wu

Theses and Dissertations--Computer Science

A common feature of emerging future Internet architectures is the ability for applications to select the path, or paths, their packets take between a source and destination. Unlike the current Internet architecture where routing protocols find a single (best) path between a source and destination, future Internet routing protocols will present applications with a set of paths and allow them to select the most appropriate path. Although this enables applications to be actively involved in the selection of the paths their packets travel, the huge number of potential paths and the need to know the current network conditions of each …

Misfit: Mining Software Fault Information And Types, Billy R. Kidwell

Theses and Dissertations--Computer Science

As software becomes more important to society, the number, age, and complexity of systems grow. Software organizations require continuous process improvement to maintain the reliability, security, and quality of these software systems. Software organizations can utilize data from manual fault classification to meet their process improvement needs, but organizations lack the expertise or resources to implement them correctly.

This dissertation addresses the need for the automation of software fault classification. Validation results show that automated fault classification, as implemented in the MiSFIT tool, can group faults of similar nature. The resulting classifications result in good agreement for common software faults …

Design Of A Scalable Path Service For The Internet, Mehmet O. Ascigil

Theses and Dissertations--Computer Science

Despite the world-changing success of the Internet, shortcomings in its routing and forwarding system have become increasingly apparent. One symptom is an escalating tension between users and providers over the control of routing and forwarding of packets: providers understandably want to control use of their infrastructure, and users understandably want paths with sufficient quality-of-service (QoS) to improve the performance of their applications. As a result, users resort to various “hacks” such as sending traffic through intermediate end-systems, and the providers fight back with mechanisms to inspect and block such traffic.

To enable users and providers to jointly control routing and …

Application Of Random Indexing To Multi Label Classification Problems: A Case Study With Mesh Term Assignment And Diagnosis Code Extraction, Yuan Lu

Theses and Dissertations--Computer Science

Many manual biomedical annotation tasks can be categorized as instances of the typical multi-label classification problem where several categories or labels from a fixed set need to assigned to an input instance. MeSH term assignment to biomedical articles and diagnosis code extraction from medical records are two such tasks. To address this problem automatically, in this thesis, we present a way to utilize latent associations between labels based on output label sets. We used random indexing as a method to determine latent associations and use the associations as a novel feature in a learning-to-rank algorithm that reranks candidate labels selected …

Multilevel Ant Colony Optimization To Solve Constrained Forest Transportation Planning Problems, Pengpeng Lin

Theses and Dissertations--Computer Science

In this dissertation, we focus on solving forest transportation planning related problems, including constraints that consider negative environmental impacts and multi-objective optimizations that provide forest managers and road planers alternatives for making informed decisions. Along this line of study, several multilevel techniques and mataheuristic algorithms have been developed and investigated. The forest transportation planning problem is a fixed-charge problem and known to be NP-hard. The general idea of utilizing multilevel approach is to solve the original problem of which the computational cost maybe prohibitive by using a set of increasingly smaller problems of which the computational cost is cheaper.

The …

Role Based Hedonic Games, Matthew Spradling

Theses and Dissertations--Computer Science

In the hedonic coalition formation game model Roles Based Hedonic Games (RBHG), agents view teams as compositions of available roles. An agent's utility for a partition is based upon which role she fulfills within the coalition and which additional roles are being fulfilled within the coalition. I consider optimization and stability problems for settings with variable power on the part of the central authority and on the part of the agents. I prove several of these problems to be NP-complete or coNP-complete. I introduce heuristic methods for approximating solutions for a variety of these hard problems. I validate heuristics on …

A Hypernet Architecture, Shufeng Huang

Theses and Dissertations--Computer Science

Network virtualization is becoming a fundamental building block of future Internet architectures. By adding networking resources into the “cloud”, it is possible for users to rent virtual routers from the underlying network infrastructure, connect them with virtual channels to form a virtual network, and tailor the virtual network (e.g., load application-specific networking protocols, libraries and software stacks on to the virtual routers) to carry out a specific task. In addition, network virtualization technology allows such special-purpose virtual networks to co-exist on the same set of network infrastructure without interfering with each other.

Although the underlying network resources needed to support …

Computational Multimedia For Video Self Modeling, Ju Shen

Theses and Dissertations--Computer Science

Video self modeling (VSM) is a behavioral intervention technique in which a learner models a target behavior by watching a video of oneself. This is the idea behind the psychological theory of self-efficacy - you can learn or model to perform certain tasks because you see yourself doing it, which provides the most ideal form of behavior modeling. The effectiveness of VSM has been demonstrated for many different types of disabilities and behavioral problems ranging from stuttering, inappropriate social behaviors, autism, selective mutism to sports training. However, there is an inherent difficulty associated with the production of VSM material. Prolonged …

Nuclei/Cell Detection In Microscopic Skeletal Muscle Fiber Images And Histopathological Brain Tumor Images Using Sparse Optimizations, Hai Su

Theses and Dissertations--Computer Science

Nuclei/Cell detection is usually a prerequisite procedure in many computer-aided biomedical image analysis tasks. In this thesis we propose two automatic nuclei/cell detection frameworks. One is for nuclei detection in skeletal muscle fiber images and the other is for brain tumor histopathological images.

For skeletal muscle fiber images, the major challenges include: i) shape and size variations of the nuclei, ii) overlapping nuclear clumps, and iii) a series of z-stack images with out-of-focus regions. We propose a novel automatic detection algorithm consisting of the following components: 1) The original z-stack images are first converted into one all-in-focus image. 2) A …

Automatic Performance Level Assessment In Minimally Invasive Surgery Using Coordinated Sensors And Composite Metrics, Sami Taha Abu Snaineh

Theses and Dissertations--Computer Science

Skills assessment in Minimally Invasive Surgery (MIS) has been a challenge for training centers for a long time. The emerging maturity of camera-based systems has the potential to transform problems into solutions in many different areas, including MIS. The current evaluation techniques for assessing the performance of surgeons and trainees are direct observation, global assessments, and checklists. These techniques are mostly subjective and can, therefore, involve a margin of bias.

The current automated approaches are all implemented using mechanical or electromagnetic sensors, which suffer limitations and influence the surgeon’s motion. Thus, evaluating the skills of the MIS surgeons and trainees …

Algorithms For Fault Tolerance In Distributed Systems And Routing In Ad Hoc Networks, Qiangfeng Jiang

Theses and Dissertations--Computer Science

Checkpointing and rollback recovery are well-known techniques for coping with failures in distributed systems. Future generation Supercomputers will be message passing distributed systems consisting of millions of processors. As the number of processors grow, failure rate also grows. Thus, designing efficient checkpointing and recovery algorithms for coping with failures in such large systems is important for these systems to be fully utilized. We presented a novel communication-induced checkpointing algorithm which helps in reducing contention for accessing stable storage to store checkpoints. Under our algorithm, a process involved in a distributed computation can independently initiate consistent global checkpointing by saving its …

Automatic Detection Of Abnormal Behavior In Computing Systems, James Frank Roberts

Theses and Dissertations--Computer Science

I present RAACD, a software suite that detects misbehaving computers in large computing systems and presents information about those machines to the system administrator. I build this system using preexisting anomaly detection techniques. I evaluate my methods using simple synthesized data, real data containing coerced abnormal behavior, and real data containing naturally occurring abnormal behavior. I find that the system adequately detects abnormal behavior and significantly reduces the amount of uninteresting computer health data presented to a system administrator.

Recovering Local Neural Tract Directions And Reconstructing Neural Pathways In High Angular Resolution Diffusion Mri, Ning Cao

Theses and Dissertations--Computer Science

Magnetic resonance imaging (MRI) is an imaging technique to visualize internal structures of the body. Diffusion MRI is an MRI modality that measures overall diffusion effect of molecules in vivo and non-invasively. Diffusion tensor imaging (DTI) is an extended technique of diffusion MRI. The major application of DTI is to measure the location, orientation and anisotropy of fiber tracts in white matter. It enables non-invasive investigation of major neural pathways of human brain, namely tractography. As spatial resolution of MRI is limited, it is possible that there are multiple fiber bundles within the same voxel. However, diffusion tensor model is …

Privacy Preserving Distributed Data Mining, Zhenmin Lin

Theses and Dissertations--Computer Science

Privacy preserving distributed data mining aims to design secure protocols which allow multiple parties to conduct collaborative data mining while protecting the data privacy. My research focuses on the design and implementation of privacy preserving two-party protocols based on homomorphic encryption. I present new results in this area, including new secure protocols for basic operations and two fundamental privacy preserving data mining protocols.

I propose a number of secure protocols for basic operations in the additive secret-sharing scheme based on homomorphic encryption. I derive a basic relationship between a secret number and its shares, with which we develop efficient secure …

Multihierarchical Documents And Fine-Grained Access Control, Neil Moore

Theses and Dissertations--Computer Science

This work presents new models and algorithms for creating, modifying, and controlling access to complex text. The digitization of texts opens new opportunities for preservation, access, and analysis, but at the same time raises questions regarding how to represent and collaboratively edit such texts. Two issues of particular interest are modelling the relationships of markup (annotations) in complex texts, and controlling the creation and modification of those texts. This work addresses and connects these issues, with emphasis on data modelling, algorithms, and computational complexity; and contributes new results in these areas of research.

Although hierarchical models of text and markup …

Measuring Effectiveness Of Address Schemes For As-Level Graphs, Yinfang Zhuang

Theses and Dissertations--Computer Science

This dissertation presents measures of efficiency and locality for Internet addressing schemes.

Historically speaking, many issues, faced by the Internet, have been solved just in time, to make the Internet just work~\cite{justWork}. Consensus, however, has been reached that today's Internet routing and addressing system is facing serious scaling problems: multi-homing which causes finer granularity of routing policies and finer control to realize various traffic engineering requirements, an increased demand for provider-independent prefix allocations which injects unaggregatable prefixes into the Default Free Zone (DFZ) routing table, and ever-increasing Internet user population and mobile edge devices. As a result, the DFZ routing …