Computer Engineering Commons^™

A Review On Mixed Criticality Methods, Alex Jenkel

Recent Advances in Real-Time Systems

Within the study of mixed criticality scheduling, there are many different aspects that must be considered—resources, processor speeds, number of processors, etc.—that make scheduling theories difficult to produce. Two papers address specific aspects of mixed criticality scheduling, and this paper compares the two different methods and also builds upon them.

Twitter And Disasters: A Social Resilience Fingerprint, Benjamin A. Rachunok, Jackson B. Bennett, Roshanak Nateghi

Purdue University Libraries Open Access Publishing Fund

Understanding the resilience of a community facing a crisis event is critical to improving its adaptive capacity. Community resilience has been conceptualized as a function of the resilience of components of a community such as ecological, infrastructure, economic, and social systems, etc. In this paper, we introduce the concept of a “resilience fingerprint” and propose a multi-dimensional method for analyzing components of community resilience by leveraging existing definitions of community resilience with data from the social network Twitter. Twitter data from 14 events are analyzed and their resulting resilience fingerprints computed. We compare the fingerprints between events and show that …

Environmental Monitoring Using A Drone-Enabled Wireless Sensor Network, Gina Valentino, Laura Yates, Brooke Potter

Senior Honors Projects, 2010-2019

Water quality monitoring traditionally occurs via resource intensive field surveys, such as when a researcher manually collects data in a stream. Limiting factors such as time, money, and accessibility often result in less oversight of impaired water bodies, significantly threatening ecosystemic health and related ecosystem services. According to the United States Environmental Protection Agency, 84% of rivers and streams within the United States remain unassessed, resulting in significant lapses in available data. Such lapses prohibit efficient and effective monitoring, restoration, and conservation efforts throughout the United States. The objective of this project was to employ an unmanned aerial vehicle to …

The Future Robo-Advisor, Catalin Burlacu

MITB Thought Leadership Series

The accelerated digitalisation of both people and business around the world today is having a huge impact on the investment management and advisory space. The addition of new and vastly larger data sets, as well as exponentially more sophisticated analytical tools to turn that data into usable information is constantly changing the way investments are decided on, made and managed.

Different Approaches To Blurring Digital Images And Their Effect On Facial Detection, Erich-Matthew Pulfer

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this thesis is to analyze the usage of multiple image blurring techniques and determine their effectiveness in combatting facial detection algorithms. This type of analysis is anticipated to reveal potential flaws in the privacy expected from blurring images or, rather, portions of images. Three different blurring algorithms were designed and implemented: a box blurring method, a Gaussian blurring method, and a differential privacy-based pixilation method. Datasets of images were collected from multiple sources, including the AT&T Database of Faces. Each of these three methods were implemented via their own original method, but, because of how common they …

Identifying Fake News Using Emotion Analysis, Brady Gilleran

Computer Science and Computer Engineering Undergraduate Honors Theses

This paper presents research applying Emotional Analysis to “Fake News” and “Real News” articles to investigate whether or not there is a difference in the emotion used in these two types of news articles. The paper reports on a dataset for Fake and Real News that we created, and the natural language processing techniques employed to process the collected text. We use a lexicon that includes predefined words for eight emotions (anger, anticipation, disgust, fear, surprise, sadness, joy, trust) to measure the emotional impact in each of these eight dimensions. The results of the emotion analysis are used as features …

Applications Of Fog Computing In Video Streaming, Kyle Smith

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this paper is to show the viability of fog computing in the area of video streaming in vehicles. With the rise of autonomous vehicles, there needs to be a viable entertainment option for users. The cloud fails to address these options due to latency problems experienced during high internet traffic. To improve video streaming speeds, fog computing seems to be the best option. Fog computing brings the cloud closer to the user through the use of intermediary devices known as fog nodes. It does not attempt to replace the cloud but improve the cloud by allowing faster …

Prototyping A Capacitive Sensing Device For Gesture Recognition, Chenglong Lin

Computer Science and Computer Engineering Undergraduate Honors Theses

Capacitive sensing is a technology that can detect proximity and touch. It can also be utilized to measure position and acceleration of gesture motions. This technology has many applications, such as replacing mechanical buttons in a gaming device interface, detecting respiration rate without direct contact with the skin, and providing gesture sensing capability for rehabilitation devices. In this thesis, an approach to prototype a capacitive gesture sensing device using the Eagle PCB design software is demonstrated. In addition, this paper tested and evaluated the resulting prototype device, validating the effectiveness of the approach.

Normally-Off Computing Design Methodology Using Spintronics: From Devices To Architectures, Arman Roohi

Electronic Theses and Dissertations

Energy-harvesting-powered computing offers intriguing and vast opportunities to dramatically transform the landscape of Internet of Things (IoT) devices and wireless sensor networks by utilizing ambient sources of light, thermal, kinetic, and electromagnetic energy to achieve battery-free computing. In order to operate within the restricted energy capacity and intermittency profile of battery-free operation, it is proposed to innovate Elastic Intermittent Computation (EIC) as a new duty-cycle-variable computing approach leveraging the non-volatility inherent in post-CMOS switching devices. The foundations of EIC will be advanced from the ground up by extending Spin Hall Effect Magnetic Tunnel Junction (SHE-MTJ) device models to realize SHE-MTJ-based …

Optimization Of Ultra-Low Power Application-Specific Asynchronous Deep Learning Integrated Circuit Design, Cole Sherrill

Computer Science and Computer Engineering Undergraduate Honors Theses

The Internet of Things (IoT) consists of all devices connected to the internet, including battery-powered devices like surveillance cameras and smart watches. IoT devices are often idle, making leakage power a crucial design constraint. Currently, there are only a few low-power application-specific processors for deep learning. Recently, the Trustable Logic Circuit Design (TruLogic) laboratory at the UofA designed an asynchronous Convolutional Neural Network (CNN) system. However, the original design suffered from delay-sensitivity issues undermining its reliable operation. The aim of this thesis research is to modify the existing CNN circuit to achieve increased reliability and to optimize the improved design …

A Machine Learning Approach To Network Intrusion Detection System Using K Nearest Neighbor And Random Forest, Ilemona S. Atawodi

Master's Theses

The evolving area of cybersecurity presents a dynamic battlefield for cyber criminals and security experts. Intrusions have now become a major concern in the cyberspace. Different methods are employed in tackling these threats, but there has been a need now more than ever to updating the traditional methods from rudimentary approaches such as manually updated blacklists and whitelists. Another method involves manually creating rules, this is usually one of the most common methods to date.

A lot of similar research that involves incorporating machine learning and artificial intelligence into both host and network-based intrusion systems recently. Doing this originally presented …

Enhanced Security System With Image Feature Identification, Musharrat Chowdhury

Publications and Research

Open source hardware and software will be used to acquire camera images and recognize and identify objects of interest in the image that would be used in new or existing personal security system. The mechanism of this system rotates either automatically or manually to track a face when a human is within view of the camera. The biometric security recognition system is a real world applications with complex effects of illumination and imaging conditions on live images.

Incentivizing Collaboration In A Competition, Arunesh Sinha, Michael P. Wellman

Research Collection School Of Computing and Information Systems

Research and design competitions aim to promote innovation or creative production, which are often best achieved through collaboration. The nature of a competition, however, typically necessitates sorting by individual performance. This presents tradeoffs for the competition designer, between incentivizing global performance and distinguishing individual capability. We model this situation in terms of an abstract collaboration game, where individual effort also benefits neighboring agents. We propose a scoring mechanism called LSWM that rewards agents based on localized social welfare. We show that LSWM promotes global performance, in that social optima are equilibria of the mechanism. Moreover, we establish conditions under which …

Crude Oil Price Prediction With Decision Tree Based Regression Approach, Engu Chen, Xin James He

Journal of International Technology and Information Management

Crude oil is an essential commodity for industry and the prediction of its price is crucial for many business entities and government organizations. While there have been quite a few conventional statistical models to forecast oil prices, we find that there is not much research using decision tree models to predict crude oil prices. In this research, we develop decision tree models to forecast crude oil prices. In addition to historical crude oil price time series data, we also use some predictor variables that would potentially affect crude oil prices, including crude oil demand and supply, and monthly GDP and …

Ipv6 Diffusion Milestones: Assessing The Quantity And Quality Of Adoption, John Pickard, Mark Angolia, Dale Drummond

Journal of International Technology and Information Management

There are currently two versions of Internet Protocol (IP) in use today, IP version 4 (IPv4) and IP version 6 (IPv6). The original version, IPv4, was standardized in the early 1980s as part of the Defense Advanced Research Project Agency Internet program and became the official Internet protocol in 1983 (Kleinrock, 2010). IPv6 was standardized in 1995 as its successor to provide enhanced capabilities and address IPv4 technological limitations, most notable of which was the anticipated exhaustion of address space (Deering & Hinden, 1995). While the two protocols have some functional similarities, they are distinct and not backward compatible; IPv4-only …

The Role Of Emotional Expression In Accessing Social Networks: The Case Of Newcomers' Blogs, Michael J. Hine, Luciara Nardon, Daniel Gulanowski

Journal of International Technology and Information Management

Research has established the critical role of social networks in facilitating adjustment to foreign environments. Increasingly, social interactions are happening through computer mediated technology. This paper explores the role of emotional expression in newcomers’ blogs in developing and interacting with social networks in a new country. This research uses a dictionary-based text analytics approach to detect emotional expression in newcomers’ blog posts and their associated discussions. Blog posts with more emotional expression had more associated responses; discussions tended to be more positive than posts; and the relative amount of negative emotion in the discussions increases as posts become more negative. …

The Most Powerful Thing, Caitlin Jankiewicz

Lake Union Herald

No abstract provided.

Image Processing Algorithms For Elastin Lamellae Inside Cardiovascular Arteries, Mahmoud Habibnezhad

School of Computing: Dissertations, Theses, and Student Research

Automated image processing methods are greatly needed to replace the tedious, manual histology analysis still performed by many physicians. This thesis focuses on pathological studies that express the essential role of elastin lamella in the resilience and elastic properties of the arterial blood vessels. Due to the stochastic nature of the shape and distribution of the elastin layers, their morphological features appear as the best candidates to develop a mathematical formulation for the resistance behavior of elastic tissues. However, even for trained physicians and their assistants, the current measurement procedures are highly error-prone and prolonged. This thesis successfully integrates such …

A Survey On The Role Of Individual Differences On Visual Analytics Interactions: Masters Project Report, Jesse Huang, Alvitta Ottley

All Computer Science and Engineering Research

There is ample evidence in the visualization commu- nity that individual differences matter. These prior works high- light various traits and cognitive abilities that can modulate the use of the visualization systems and demonstrate a measurable influence on speed, accuracy, process, and attention. Perhaps the most important implication of this body of work is that we can use individual differences as a mechanism for estimating people’s potential to effectively leverage visual interfaces or to identify those people who may struggle. As visual literacy and data fluency continue to become essential skills for our everyday lives, we must embrace the growing …

Smart Home Audio Assistant, Xipeng Wang

All Computer Science and Engineering Research

This report introduces an audio processing algorithm. It provides a way to access smart devices using audio. Although there are many audio assistants already on the market, most of them will not be able to control the smart devices. Therefore, this new system presented in this report will provide a way to analysis the customer’s questions. Then the algorithm will be able to query smart device information, modify the schedule or provide the reason for some arrangement.

Operating Systems Laboratory, Emt 2390l, Course Outline, Jose Reyes Alamo

Open Educational Resources

Students study the characteristics of operating systems used in IBM systems. They learn how to install the operating systems and set it up to control the computer hardware. They also learn to use the features of the operating systems to manage the computer system.

Heterogeneous Reconfigurable Fabrics For In-Circuit Training And Evaluation Of Neuromorphic Architectures, Ramtin Mohammadizand

Electronic Theses and Dissertations

A heterogeneous device technology reconfigurable logic fabric is proposed which leverages the cooperating advantages of distinct magnetic random access memory (MRAM)-based look-up tables (LUTs) to realize sequential logic circuits, along with conventional SRAM-based LUTs to realize combinational logic paths. The resulting Hybrid Spin/Charge FPGA (HSC-FPGA) using magnetic tunnel junction (MTJ) devices within this topology demonstrates commensurate reductions in area and power consumption over fabrics having LUTs constructed with either individual technology alone. Herein, a hierarchical top-down design approach is used to develop the HSCFPGA starting from the configurable logic block (CLB) and slice structures down to LUT circuits and the …

Leveraging The Intrinsic Switching Behaviors Of Spintronic Devices For Digital And Neuromorphic Circuits, Steven Pyle

Electronic Theses and Dissertations

With semiconductor technology scaling approaching atomic limits, novel approaches utilizing new memory and computation elements are sought in order to realize increased density, enhanced functionality, and new computational paradigms. Spintronic devices offer intriguing avenues to improve digital circuits by leveraging non-volatility to reduce static power dissipation and vertical integration for increased density. Novel hybrid spintronic-CMOS digital circuits are developed herein that illustrate enhanced functionality at reduced static power consumption and area cost. The developed spin-CMOS D Flip-Flop offers improved power-gating strategies by achieving instant store/restore capabilities while using 10 fewer transistors than typical CMOS-only implementations. The spin-CMOS Muller C-Element developed …

Value-Of-Information Based Data Collection In Underwater Sensor Networks, Fahad Khan

Electronic Theses and Dissertations

Underwater sensor networks are deployed in marine environments, presenting specific challenges compared to sensor networks deployed in terrestrial settings. Among the major issues that underwater sensor networks face is communication medium limitations that result in low bandwidth and long latency. This creates problems when these networks need to transmit large amounts of data over long distances. A possible solution to address this issue is to use mobile sinks such as autonomous underwater vehicles (AUVs) to offload these large quantities of data. Such mobile sinks are called data mules. Often it is the case that a sensor network is deployed to …

Granny Pod Virtual Assistant, David Connolly, Bing Chen

Theses/Capstones/Creative Projects

Dr. Chen is working on a sustainable small house (SSH) project, sometimes called the “Granny Pod”. Regulations will soon allow homeowners to house their parents on their property, which can be an opportunity live independently in a cheap, sustainable, and convenient alternative to a retirement community. To help achieve this vision, a Virtual Assistant system for the SSH was developed. The system uses a Google Home or Amazon Echo to respond to the voice command “Hey Google (or Alexa), I need help” by contacting the nearby homeowner or caretaker. It alerts the resident who is at the door when the …

A Data-Driven Approach For Detecting Stress In Plants Using Hyperspectral Imagery, Suraj Gampa

School of Computing: Dissertations, Theses, and Student Research

A phenotype is an observable characteristic of an individual and is a function of its genotype and its growth environment. Individuals with different genotypes are impacted differently by exposure to the same environment. Therefore, phenotypes are often used to understand morphological and physiological changes in plants as a function of genotype and biotic and abiotic stress conditions. Phenotypes that measure the level of stress can help mitigate the adverse impacts on the growth cycle of the plant. Image-based plant phenotyping has the potential for early stress detection by means of computing responsive phenotypes in a non-intrusive manner. A large number …

Classification Of The 4 Stages Of Diabetic Retinopathy Using A Low Complexity Convolutional Neural Network., Zeliha Ogur

Electronic Theses and Dissertations

Diabetic Retinopathy is an eye disease that affects the blood vessels of the retina tissue found in the back of the eye. The blood vessels in the retina discharge fluid or cause hemorrhage when affected by diabetic retinopathy. It leads to loss of eye vision with people with diabetics and also among working adults. The disease may advance in four stages which include Mild nonproliferative, moderate nonproliferative, severe nonproliferative and proliferative diabetic retinopathy. In the mild stage also known as background retinopathy, lumps occur in the blood vessel and distort a little amount of blood. At this stage, you are …

Hardware Ip Classification Through Weighted Characteristics, Brendan Mcgeehan

Graduate Theses and Dissertations

Today’s business model for hardware designs frequently incorporates third-party Intellectual Property (IP) due to the many benefits it can bring to a company. For instance, outsourcing certain components of an overall design can reduce time-to-market by allowing each party to specialize and perfect a specific part of the overall design. However, allowing third-party involvement also increases the possibility of malicious attacks, such as hardware Trojan insertion. Trojan insertion is a particularly dangerous security threat because testing the functionality of an IP can often leave the Trojan undetected. Therefore, this thesis work provides an improvement on a Trojan detection method known …

Interoperable E-Infrastructure Services In Arabia, Salem Al-Agtash, Roberto Barbera

Computer Science and Engineering

e-Infrastructures became critical platforms that integrate computational resources, facilities and repositories globally. The coordination and harmonization of advanced e-Infrastructure project developed with partners from Europe, Latin America, Arabia, Africa, China, and India contributed to developing interoperable platforms based on identity federation and science gateway technologies. This paper presents these technologies to support key services in the development of Arabia networking and services platform for research and education. The platform provides scientists, teachers, and students with seamless access to a variety of advanced resources, services, and applications available at regional e-Infrastructures in Europe and elsewhere. Users simply enter the credentials provided …

Segmentation And Classification Of Lung Nodules From Thoracic Ct Scans : Methods Based On Dictionary Learning And Deep Convolutional Neural Networks., Mohammad Mehdi Farhangi

Electronic Theses and Dissertations

Lung cancer is a leading cause of cancer death in the world. Key to survival of patients is early diagnosis. Studies have demonstrated that screening high risk patients with Low-dose Computed Tomography (CT) is invaluable for reducing morbidity and mortality. Computer Aided Diagnosis (CADx) systems can assist radiologists and care providers in reading and analyzing lung CT images to segment, classify, and keep track of nodules for signs of cancer. In this thesis, we propose a CADx system for this purpose. To predict lung nodule malignancy, we propose a new deep learning framework that combines Convolutional Neural Networks (CNN) and …