Other Computer Engineering Commons^™

Wide-Area Measurement-Driven Approaches For Power System Modeling And Analytics, Hesen Liu

Doctoral Dissertations

This dissertation presents wide-area measurement-driven approaches for power system modeling and analytics. Accurate power system dynamic models are the very basis of power system analysis, control, and operation. Meanwhile, phasor measurement data provide first-hand knowledge of power system dynamic behaviors. The idea of building out innovative applications with synchrophasor data is promising.

Taking advantage of the real-time wide-area measurements, one of phasor measurements’ novel applications is to develop a synchrophasor-based auto-regressive with exogenous inputs (ARX) model that can be updated online to estimate or predict system dynamic responses.

Furthermore, since auto-regressive models are in a big family, the ARX model …

A Probabilistic Software Framework For Scalable Data Storage And Integrity Check, Sisi Xiong

Doctoral Dissertations

Data has overwhelmed the digital world in terms of volume, variety and velocity. Data- intensive applications are facing unprecedented challenges. On the other hand, computation resources, such as memory, suffer from shortage comparing to data scale. However, in certain applications, it is a must to process large amount of data in a time efficient manner. Probabilistic approaches are compromises between these three perspectives: large amount of data, limited computation resources and high time efficiency, in the sense that those approaches cannot guarantee 100% correctness, their error rates, however, are predictable and adjustable depending on available computation resources and time constraints. …

Computer-Aided Detection Of Pathologically Enlarged Lymph Nodes On Non-Contrast Ct In Cervical Cancer Patients For Low-Resource Settings, Brian M. Anderson, Laurence E. Court, Ann Klopp, Stephen F. Kry, Jennifer Johnson, Erik Cressman, Arvind Rao, Jinzhong Yang

Dissertations & Theses (Open Access)

The mortality rate of cervical cancer is approximately 266,000 people each year, and 70% of the burden occurs in Low- and Middle- Income Countries (LMICs). Radiation therapy is the primary modality for treatment of locally advanced cervical cancer cases. In the absence of high quality diagnostic imaging needed to identify nodal metastasis, many LMIC sites treat standard pelvic fields, failing to include node metastasis outside of the field and/or to boost lymph nodes in the abdomen and pelvis. The first goal of this project was to create a program which automatically identifies positive cervical cancer lymph nodes on non-contrast daily …

Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi

Electronic Theses and Dissertations

While understanding of machine learning and data mining is still in its budding stages, the engineering applications of the same has found immense acceptance and success. Cybersecurity applications such as intrusion detection systems, spam filtering, and CAPTCHA authentication, have all begun adopting machine learning as a viable technique to deal with large scale adversarial activity. However, the naive usage of machine learning in an adversarial setting is prone to reverse engineering and evasion attacks, as most of these techniques were designed primarily for a static setting. The security domain is a dynamic landscape, with an ongoing never ending arms race …

Prediction Of Graduation Delay Based On Student Characterisitics And Performance, Tushar Ojha

Electrical and Computer Engineering ETDs

A college student's success depends on many factors including pre-university characteristics and university student support services. Student graduation rates are often used as an objective metric to measure institutional effectiveness. This work studies the impact of such factors on graduation rates, with a particular focus on delay in graduation. In this work, we used feature selection methods to identify a subset of the pre-institutional features with the highest discriminative power. In particular, Forward Selection with Linear Regression, Backward Elimination with Linear Regression, and Lasso Regression were applied. The feature sets were selected in a multivariate fashion. High school GPA, ACT …

Distributed Knowledge Discovery For Diverse Data, Hossein Hamooni

Computer Science ETDs

In the era of new technologies, computer scientists deal with massive data of size hundreds of terabytes. Smart cities, social networks, health care systems, large sensor networks, etc. are constantly generating new data. It is non-trivial to extract knowledge from big datasets because traditional data mining algorithms run impractically on such big datasets. However, distributed systems have come to aid this problem while introducing new challenges in designing scalable algorithms. The transition from traditional algorithms to the ones that can be run on a distributed platform should be done carefully. Researchers should design the modern distributed algorithms based on the …

Virtualization Of Closed-Loop Sensor Networks, Priyanka Dattatri Kedalagudde

Masters Theses

The existing closed-loop sensor networks are based on architectures that are designed and implemented for one specific application and require dedicated sensing and computational resources. This prevents the sharing of these networks. In this work, we propose an architecture of virtualization to allow sharing of closed-loop sensor networks. We also propose a scheduling approach that will manage requests from competing applications and evaluate their impact on system utilization against utilization achieved by more traditional, dedicated sensor networks. These algorithms are evaluated through trace-driven simulations, where the trace data is taken from CASA’s closed-loop weather radar sensor network. Results from this …

Large-Scale Flexible Membrane For Automatic Strain Monitoring Of Transportation Infrastructure, Simon Laflamme, Venkata D. Kolipara, Hussam S. Saleem, Randall L. Geiger

Randall Geiger

Structural Health Monitoring (SHM) of transportation infrastructures is a complex task, typically conducted by visual inspection due to the technical and economical constrains of existing health monitoring technologies. It results that health monitoring is highly dependent on scheduling and on the judgment of the inspectors, which can be costly and ineffective. Thus, it is fundamental to automate the SHM process to allow timely inspection, maintenance, and management of transportation infrastructure. The authors propose a flexible membrane that can be deployed over large surfaces, at low cost, for automatic and continuous monitoring of strains. The membrane, termed sensing skin, is constituted …

One-To-Cloud One-Time Pad Data Encryption: Introducing Virtual Prototyping With Pspice, Paul Tobin, Lee Tobin, Roberto Gandia Blanquer Dr, Michael Mckeever, Jonathan Blackledge

Conference papers

In this paper, we examine the design and application of a one-time pad encryption system for protecting data stored in the Cloud. Personalising security using a one-time pad generator at the client-end protects data from break-ins, side-channel attacks and backdoors in public encryption algorithms. The one-time pad binary sequences were obtained from modified analogue chaos oscillators initiated by noise and encoded client data locally. Specific ``one-to-Cloud'' storage applications returned control back to the end user but without the key distribution problem normally associated with one-time pad encryption. Development of the prototype was aided by ``Virtual Prototyping'' in the latest version …

Multiple-Phase Modeling Of Degradation Signal For Condition Monitoring And Remaining Useful Life Prediction, Yuxin Wen, Jianguo Wu, Yuan Yuan

Engineering Faculty Articles and Research

Remaining useful life prediction plays an important role in ensuring the safety, availability, and efficiency of various engineering systems. In this paper, we propose a flexible Bayesian multiple-phase modeling approach to characterize degradation signals for prognosis. The priors are specified with a novel stochastic process and the multiple-phase model is formulated to a novel state-space model to facilitate online monitoring and prediction. A particle filtering algorithm with stratified sampling and partial Gibbs resample-move strategy is developed for online model updating and residual life prediction. The advantages of the proposed method are demonstrated through extensive numerical studies and real case studies.

The Engineering Admissions Partnership Program: A Navigation Strategy For Community College Students Seeking A Pathway Into Engineering, Marcia R. Laugerman, Mack C. Shelley, Steven K. Mickelson, Diane T. Rover

Diane Rover

This paper presents the evaluation of a program designed to improve transfer outcomes for community college students pursuing an engineering degree. The program, the Engineering Admissions Partnership Program (E-APP), was designed to improve the navigational success of community college transfer students through connections to the university. These connections include coordinated academic advising, peer-mentoring, campus visits, and online social and professional networks. The objective of the study is to determine the efficacy of the E-APP and its interventions, which will be measured by increased participation rates and increased university retention rates for E-APP participants. Outcome data for the students are analyzed …

Farmbot Rfid Integration, Laura R. Swart

Computer Engineering

The purpose of this project is to assist the company FarmBot improve their product by adding RFID tracking to the FarmBot robot. RFID tracking will allow the robot to select and pick up tool heads without any user interference.

Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto

Computer Engineering

The Underwater Computer Vision – Fish Recognition project includes the design and implementation of a device that can withstand staying underwater for a duration of time, take pictures of underwater creatures, such as fish, and be able to identify certain fish. The system is meant to be cheap to create, yet still able to process the images it takes and identify the objects in the pictures with some accuracy. The device can output its results to another device or an end user.

Multispectral Identification Array, Zachary D. Eagan

Computer Engineering

The Multispectral Identification Array is a device for taking full image spectroscopy data via the illumination of a subject with sixty-four unique spectra. The array combines images under the illumination spectra to produce an approximate reflectance graph for every pixel in a scene. Acquisition of an entire spectrum allows the array to differentiate objects based on surface material. Spectral graphs produced are highly approximate and should not be used to determine material properties, however the output is sufficiently consistent to allow differentiation and identification of previously sampled subjects. While not sufficiently advanced for use as a replacement to spectroscopy the …

A Survey Of Addictive Software Design, Chauncey J. Neyman

Computer Science and Software Engineering

The average smartphone owner checks their phone more than 150 times per day. As of 2015, 62% of smartphone users had used their phone to look up information about a health condition, while 57% had used their phone to do online banking. Mobile platforms have become the dominant medium of human-computer interaction. So how have these devices established themselves as our go to connection to the Internet? The answer lies in addictive design. Software designers have become well versed in creating software that captivates us at a primal level. In this article, we survey addictive software design strategies, their bases …

Djukebox: A Mobile Application Senior Project, Alexander M. Mitchell

Computer Science and Software Engineering

I’m going to discuss the process used to research, design, and develop a mobile application to handle song requests from patrons to disc jockeys. The research phase was completed in the first half of the project, during CSC-491, along with much of the design. The rest of the design and all of the development was completed during CSC-492. Once development began there were times when reverting back to the design phase was needed, which became apparent as more was learned about the mobile platform chosen for development, Android, and the backend server utilized, Google Firebase. Ultimately the project was purely …

Diy Grip Tape Website, Jason E. Krein

Computer Science and Software Engineering

The goal of this senior project was to create an easy to use website that will allow people to design and order their own custom skateboard grip tape. Custom skateboard decks are a large business, however the top, more visible, part of the board is largely ignored by custom shops. With the help of a local entrepreneur, I aim to enable skateboarders the ability to get custom grip tape shapes that they can stick on their board to spice it up from the normal black tape that everyone uses. The website was completed over the course of 4 months, in …

Daily Dose, Ken H. Yasui, Joey M. Angeja

Computer Engineering

The project goal is to develop a medication and vitamin management device that will sort and dispense pre-configured amounts of pills at designated times . The main clientele of this device is the elderly community with a secondary client base of the general public. The entire system is designed from scratch, powered by US standard line voltage. The main functionalities of the device are the ability to store multiple types of pills and the ability to accurately handle user input and data transfer. The two engineering specifications that were not met included the desired pill pick up rate and dimensions …

Cpu Db Data Visualization, Ruchita Patel, Marek Moreno

Computer Engineering

Given the CPU database from Stanford, we wanted to create something that portrayed the data in a more visually pleasing way. The CPU database website wanted a web page that would allow users to create graphs based on the processor data from the database. The web page would allow users to select different data from the database and create the graphs they wanted to gain insight into the decades of processor data.

Sublimesurf, Nathan Sfard, Karis Russell

Computer Engineering

Surf conditions change rapidly day to day and location to location, which forces modern day surfers to utilize online forecasts and obtain a detailed knowledge of the places they want to surf. To ease this pain, we are developing SublimeSurf, an iOS application that will keep track of the current surf conditions and allow users to rate aspects of the surf. We plan to use this rating data in combination with surf forecast data available online to notify a user when conditions look favorable, based on their previous ratings. We also intend to mine the data submitted by all users …

Slither.Io Deep Learning Bot, James Caudill

Computer Engineering

Recent advances in deep learning and computer vision techniques and algorithms have inspired me to create a model application. The game environment used is Slither.io. The system has no previous understanding of the game and is able to learn its surroundings through feature detection and deep learning. Contrary to other agents, my bot is able to dynamically learn and react to its environment. It operates extremely well in early game, with little enemy encounters. It has difficulty transitioning to middle and late game due to limited training time. I will continue to develop this algorithm.

Micro-Spi Sediment Profile Imaging Micro-Inspector, Andrew P. Corvin, Caleb T. Davies, Matt R. Ferrari

Mechanical Engineering

This project was proposed by Dr. Brian Paavo through a desire to more easily study the benthic sediment layers of the ocean. To do so, he asked us to build a simple and compact machine for use in sediment profile imagery (SPI). Although devices like this already exist, they are all large scale devices that require a ship with a crane to deploy, which is expensive and time consuming. Instead, he desired a “micro” SPI, which is capable of being deployed from a small vessel that can easily navigate shallow waters. Our interpretation of these requirements was as follows: a …

Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, Kyle Tanemura, Michael Li, Erica Dorn, Ryan Mckinney

Computer Science and Software Engineering

Gridiron Gurus is a desktop application that allows for the creation of custom AI profiles to help advise and compete against in a Fantasy Football setting. Our AI are capable of performing statistical prediction of players on both a season long and week to week basis giving them the ability to both draft and manage a fantasy football team throughout a season.

Design And Implementation Of An Archetype Based Interoperable Knowledge Eco-System For Data Buoys, Paul Stacey, Damon Berry

Conference papers

This paper describes the ongoing work of the authors in translating two-level system design techniques used in Health Informatics to the Earth Systems Science domain. Health informaticians have developed a sophisticated two-level systems design approach for electronic health documentation over many years, and with the use of archetypes, have shown how knowledge interoperability among heterogeneous systems can be achieved. Translating two-level modelling techniques to a new domain is a complex task. A proof-of-concept archetype enabled data buoy eco-system is presented. The concept of operational templates-as-a service is proposed. Design recommendations and implementation experiences of re-working the proposed architecture to run …

Improving A Particle Swarm Optimization-Based Clustering Method, Sharif Shahadat

University of New Orleans Theses and Dissertations

This thesis discusses clustering related works with emphasis on Particle Swarm Optimization (PSO) principles. Specifically, we review in detail the PSO clustering algorithm proposed by Van Der Merwe & Engelbrecht, the particle swarm clustering (PSC) algorithm proposed by Cohen & de Castro, Szabo’s modified PSC (mPSC), and Georgieva & Engelbrecht’s Cooperative-Multi-Population PSO (CMPSO). In this thesis, an improvement over Van Der Merwe & Engelbrecht’s PSO clustering has been proposed and tested for standard datasets. The improvements observed in those experiments vary from slight to moderate, both in terms of minimizing the cost function, and in terms of run time.

Real Time Learning Level Assessment Using Eye Tracking, Saurin S. Parikh, Hari Kalva

MODVIS Workshop

E-Learning is emerging as a convenient and effective learning tool. However, the challenge with eLearning is the lack of effective tools to assess levels of learning. Ability to predict difficult content in real time enables eLearning systems to dynamically provide supplementary content to meet learners’ needs. Recent developments have made possible low-cost eye trackers, which enables a new class of applications based on eye response. In comparison to past attempts using bio-metrics in learning assessments, with eye tracking, we can have access to the exact stimulus that is causing the response. A key aspect of the proposed approach is the …

Open Source Database And Website To Provide Free And Open Access To Inactive U.S. Patents In The Public Domain, Yuenyong Nilsiam, Joshua M. Pearce

Joshua M. Pearce

Although theoretically the patent system is meant to bolster innovation, the current United States Patent and Trademark Office (USPTO) is cumbersome and involves a significant time investment to locate inactive patents less than 20 years old. This article reports on the development of an open source database to find these public domain ideas. First, a search strategy is explained. Then the operation and use of free and open source software are detailed to meet the needs of open hardware innovators. Finally, a case study is presented to demonstrate the utility of the approach with 3-D printing. The results showed how …

Source Anonymization Of Digital Images: A Counter–Forensic Attack On Prnu Based Source Identification Techniques, Prithviraj Sengupta, Venkata Udaya Sameer, Ruchira Naskar, Ezhil Kalaimannan

Annual ADFSL Conference on Digital Forensics, Security and Law

A lot of photographers and human rights advocates need to hide their identity while sharing their images on the internet. Hence, source–anonymization of digital images has become a critical issue in the present digital age. The current literature contains a number of digital forensic techniques for “source–identification” of digital images, one of the most efficient of them being Photo–Response Non–Uniformity (PRNU) sensor noise pattern based source detection. PRNU noise pattern being unique to every digital camera, such techniques prove to be highly robust way of source–identification. In this paper, we propose a counter–forensic technique to mislead this PRNU sensor noise …

An Accidental Discovery Of Iot Botnets And A Method For Investigating Them With A Custom Lua Dissector, Max Gannon, Gary Warner, Arsh Arora

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper presents a case study that occurred while observing peer-to-peer network communications on a botnet monitoring station and shares how tools were developed to discover what ultimately was identified as Mirai and many related IoT DDOS Botnets. The paper explains how researchers developed a customized protocol dissector in Wireshark using the Lua coding language, and how this enabled them to quickly identify new DDOS variants over a five month period of study.

Classification Of Images Based On Pixels That Represent A Small Part Of The Scene. A Case Applied To Microaneurysms In Fundus Retina Images, Pablo F. Ordonez, Pablo F. Ordonez

Master of Science in Computer Science Theses

Convolutional Neural Networks (CNNs), the state of the art in image classification, have proven to be as effective as an ophthalmologist, when detecting Referable Diabetic Retinopathy (RDR). Having a size of less than 1\% of the total image, microaneurysms are early lesions in DR that are difficult to classify. The purpose of this thesis is to improve the accuracy of detection of microaneurysms using a model that includes two CNNs with different input image sizes, 60x60 and 420x420 pixels. These models were trained using the Kaggle and Messidor datasets and tested independently against the Kaggle dataset, showing a sensitivity of …