Computer Engineering Commons^™

Exploiting Alignments In Linked Data For Compression And Query Answering, Amit Krishna Joshi

Browse all Theses and Dissertations

Linked data has experienced accelerated growth in recent years due to its interlinking ability across disparate sources, made possible via machine-processable RDF data. Today, a large number of organizations, including governments and news providers, publish data in RDF format, inviting developers to build useful applications through reuse and integration of structured data. This has led to tremendous increase in the amount of RDF data on the web. Although the growth of RDF data can be viewed as a positive sign for semantic web initiatives, it causes performance bottlenecks for RDF data management systems that store and provide access to data. …

Reducing Side-Sweep Accidents With Vehicle-To-Vehicle Communications, Gamini Bulumulle

Electronic Theses and Dissertations

This dissertation present contributions to the understanding of the causes of a side-sweep accidents on multi-lane highways using computer simulation. Side-sweep accidents are one of the major causes of loss of life and property damage on highways. This type of accident is caused by a driver initiating a lane change while another vehicle is blocking the road in the target lane. Our objective in the research described in this dissertation was to understand and simulate the different factors which affect the likelihood of side sweep accidents. For instance, we know that blind spots, parts of the road that are not …

Hoeffding Tree Algorithms For Anomaly Detection In Streaming Datasets: A Survey, Asmah Muallem, Sachin Shetty, Jan W. Pan, Juan Zhao, Biswajit Biswal

Computational Modeling & Simulation Engineering Faculty Publications

This survey aims to deliver an extensive and well-constructed overview of using machine learning for the problem of detecting anomalies in streaming datasets. The objective is to provide the effectiveness of using Hoeffding Trees as a machine learning algorithm solution for the problem of detecting anomalies in streaming cyber datasets. In this survey we categorize the existing research works of Hoeffding Trees which can be feasible for this type of study into the following: surveying distributed Hoeffding Trees, surveying ensembles of Hoeffding Trees and surveying existing techniques using Hoeffding Trees for anomaly detection. These categories are referred to as compositions …

Secrecy Rates And Optimal Power Allocation For Full-Duplex Decode-And-Forward Relay Wire-Tap Channels, Lubna Elsaid, Leonardo Jimenez-Rodriguez, Nghi H. Tran, Sachin Shetty, Shivakumar Sastry

Computational Modeling & Simulation Engineering Faculty Publications

This paper investigates the secrecy rates and optimal power allocation schemes for a decode-and-forward wiretap relay channel where the transmission from a source to a destination is aided by a relay operating in a full-duplex (FD) mode under practical residual self-interference. By first considering static channels, we address the non-convex optimal power allocation problems between the source and relay nodes under individual and joint power constraints to establish closed-form solutions. An asymptotic analysis is then given to provide important insights on the derived power allocation solutions. Specifically, by using the method of dominant balance, it is demonstrated that full power …

A New Approach To Pulse Deinterleaving Based On Adaptive Thresholding, Mostafa Bagheri, Mohammad Hossein Sedaaghi

Turkish Journal of Electrical Engineering and Computer Sciences

Since histogram-based methods are formed by some simple differences, they are very desirable for deinterleaving. However, their main imperfection concerns recognizing complex pulse repetition interval (PRI) patterns like jittered and staggered ones.In this paper, we present new thresholds to detect jittered and staggered PRI from histogram-based methods even in complex circumstances such as noisy time of arrival (TOA), complex PRI patterns, and large missing pulses. Simulation results demonstrate that our method can detect and extract constant, jittered, and staggered PRI correctly. Moreover, the method is proved to be considerably robust and reliable at a missing pulses rate up to 30%.

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 …

Autonomous Quadrotor Collision Avoidance And Destination Seeking In A Gps-Denied Environment, Thomas C. Kirven

Theses and Dissertations--Mechanical and Aerospace Engineering

This thesis presents a real-time autonomous guidance and control method for a quadrotor in a GPS-denied environment. The quadrotor autonomously seeks a destination while it avoids obstacles whose shape and position are initially unknown. We implement the obstacle avoidance and destination seeking methods using off-the-shelf sensors, including a vision-sensing camera. The vision-sensing camera detects the positions of points on the surface of obstacles. We use this obstacle position data and a potential-field method to generate velocity commands. We present a backstepping controller that uses the velocity commands to generate the quadrotor's control inputs. In indoor experiments, we demonstrate that the …

Towards High-Efficiency Data Management In The Next-Generation Persistent Memory System, Xunchao Chen

Electronic Theses and Dissertations

For the sake of higher cell density while achieving near-zero standby power, recent research progress in Magnetic Tunneling Junction (MTJ) devices has leveraged Multi-Level Cell (MLC) configurations of Spin-Transfer Torque Random Access Memory (STT-RAM). However, in order to mitigate the write disturbance in an MLC strategy, data stored in the soft bit must be restored back immediately after the hard bit switching is completed. Furthermore, as the result of MTJ feature size scaling, the soft bit can be expected to become disturbed by the read sensing current, thus requiring an immediate restore operation to ensure the data reliability. In this …

End To End Brain Fiber Orientation Estimation Using Deep Learning, Nandakishore Puttashamachar

Electronic Theses and Dissertations

In this work, we explore the various Brain Neuron tracking techniques, one of the most significant applications of Diffusion Tensor Imaging. Tractography is a non-invasive method to analyze underlying tissue micro-structure. Understanding the structure and organization of the tissues facilitates a diagnosis method to identify any aberrations which can occur within tissues due to loss of cell functionalities, provides acute information on the occurrences of brain ischemia or stroke, the mutation of certain neurological diseases such as Alzheimer, multiple sclerosis and so on. Under all these circumstances, accurate localization of the aberrations in efficient manner can help save a life. …

Energy-Aware Data Movement In Non-Volatile Memory Hierarchies, Navid Khoshavi Najafabadi

Electronic Theses and Dissertations

While technology scaling enables increased density for memory cells, the intrinsic high leakage power of conventional CMOS technology and the demand for reduced energy consumption inspires the use of emerging technology alternatives such as eDRAM and Non-Volatile Memory (NVM) including STT-MRAM, PCM, and RRAM. The utilization of emerging technology in Last Level Cache (LLC) designs which occupies a signifcant fraction of total die area in Chip Multi Processors (CMPs) introduces new dimensions of vulnerability, energy consumption, and performance delivery. To be specific, a part of this research focuses on eDRAM Bit Upset Vulnerability Factor (BUVF) to assess vulnerable portion of …

Proving Non-Deterministic Computations In Agda, Sergio Antoy, Michael Hanus, Steven Libby

Computer Science Faculty Publications and Presentations

We investigate proving properties of Curry programs using Agda. First, we address the functional correctness of Curry functions that, apart from some syntactic and semantic differences, are in the intersection of the two languages. Second, we use Agda to model non-deterministic functions with two distinct and competitive approaches incorporating the non-determinism. The first approach eliminates non-determinism by considering the set of all non-deterministic values produced by an application. The second approach encodes every non-deterministic choice that the application could perform. We consider our initial experiment a success. Although proving properties of programs is a notoriously difficult task, the functional logic …

Real-Time Pricing Strategy Based On The Stability Of Smart Grid For Green Internet Of Things, Huwei Chen, Hui Hui, Zhou Su, Dongfeng Fang, Yilong Hui

Department of Electrical and Computer Engineering: Faculty Publications

The ever increasing demand of energy efficiency and the strong awareness of environment have led to the enhanced interests in green Internet of things (IoTs). How to efficiently deliver power, especially, with the smart grid based on the stability of network becomes a challenge for green IoTs. Therefore, in this paper we present a novel real-time pricing strategy based on the network stability in the green IoTs enabled smart grid. Firstly, the outage is analyzed by considering the imbalance of power supply and demand as well as the load uncertainty. Secondly, the problem of power supply with multiple-retailers is formulated …

Implementing Software Lab At Hackathons, Istvan Gates

Williams Honors College, Honors Research Projects

Hackathons are events where groups of college students have 24 hours to build up a any project, using Computer Science and Electrical Engineering skillsets. These events are typically hosted on college campuses, and attract over 200 students per event. Each student brings 2 devices - their phone, and their laptop. That means that 400 devices are connected to a University venue's Internet network, commonly overloading it. Software Lab alleviates this overloading by providing an abstracted NAS node network for events. Software Lab guarantees speeds of at least 100 mbits/s, and provides a 8-10x improvement on download speeds over the common …

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 …

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 …

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 …

Towards Improving Visqol (Virtual Speech Quality Objective Listener) Using Machine Learning Techniques, Joseph Mcnally

Dissertations

Vast amounts of sound data are transmitted every second over digital networks. VoIP services and cellular networks transmit speech data in increasingly greater volumes. Objective sound quality models provide an essential function to measure the quality of this data in real-time. However, these models can suffer from a lack of accuracy with various degradations over networks. This research uses machine learning techniques to create one support vector regression and three neural network mapping models for use with ViSQOLAudio. Each of the mapping models (including ViSQOL and ViSQOLAudio) are tested against two separate speech datasets in order to comparatively study accuracy …

Critical Comparison Of The Classification Ability Of Deep Convolutional Neural Network Frameworks With Support Vector Machine Techniques In The Image Classification Process, Robert Kelly

Dissertations

Recently, a number of new image classification models have been developed to diversify the number of options available to prospective machine learning classifiers, such as Deep Learning. This is particularly important in the field of medical image classification as a misdiagnosis could have a severe impact on the patient. However, an assessment on the level to which a deep learning based Convolutional Neural Network can outperform a Support Vector Machine has not been discussed. In this project, the use of CNN and SVM classifiers is used on a dataset of approx. 55,000 images. This dataset was used to assess the …

An Exploration Study Of Using The Universities Performance And Enrolments Features For Predicting The International Quality, Aeshah Althagafi

Dissertations

Quality ranking systems are crucial in the assessment of the academic performance of an institution because these assessment systems give details about how different learning institutions deliver their services. Education quality is also of paramount importance to the students because it is through quality education that these students develop skills that are needed in the job market. Besides, education enhances a student's academic and reasoning capacities. When universities are subjected to ranking systems, they are likely to improve their quality to be ranked high in the system. When the university administrators are exposed to ranking, competition gears up. Through competition, …

Exploring The Factors That Affect Secondary Student’S Mathematics And Portuguese Performance In Portugal, Lulu Cheng

Dissertations

Secondary education provides not only knowledge and skills, but also inculcates values, training of instincts, fostering right attitude and habits to enable adolescents to move into tertiary education or to ensure a workplace for students who decided to terminate their secondary schooling. Without secondary education to guide the development of young people through their adolescence, they will be ill prepared for tertiary education or for workplace, moreover, the possibility of juvenile delinquency and teenage pregnancy becomes higher. These negative effects will increase the pressures and expenditures on society and socio-economic. In 2006, Portugal was reported having the higher school-leaving rate …