Other Computer Engineering Commons^™

Evaluating Creative Choice In K-12 Computer Science Curriculum, Kirsten L. Mork

Master's Theses

Computer Science is an increasingly important topic in K-12 education. Ever since the "computing crisis" of the early 2000s, where enrollment in CS dropped by over half in a five year span, increasing research has gone into improving and broadening enrollment in CS courses. Research shows the importance of introducing CS at a young age and the need for more exposure for younger children and young adults alike in order to work towards equity in the field. While there are many reasons for disinterest in CS courses, studies found one reason young adults do not want to study CS is …

Long Term Software Quality And Reliability Assurance In A Small Company, Eric Abuta

Computer Science and Engineering Theses and Dissertations

Demonstrating software reliability across multiple software releases has become essential in making informed decisions of upgrading software releases without impacting significantly end users' characterized processes and software quality standards. Standard defect and workload data normally collected in a typical small software development organization can be used for this purpose. Objective of this study was to demonstrate how to measure software reliability in multiple releases and whether continuous defect fixes and code upgrades increased software reliability. This study looked at techniques such as trend test that evaluated software system's overall trend and stability, input domain reliability models (IDRM) that assessed system's …

Quantified Measurement Of The Tilt Effect In A Family Of Café Wall Illusions, Nasim Nematzadeh Dr., David Martin Powers Prof.

MODVIS Workshop

This abstract explores the tilt effect in a family of Café Wall illusions using a Classical Gaussian Receptive Field model (CRF). Our model constructs an intermediate representation called edge map at multiple scales (Fig. 1) that reveals tilt cues and clues involved in the illusory perception of the Café Wall pattern. We investigate a wide range of parameters of the stimulus including mortar width, luminance, tiles contrast, and phase of the tile displacement (the stimuli in Fig. 2). We show that this simple bioplausible model, simulating the contrast sensitivity of the retinal ganglion cells, can not only detect the tilts …

Self-Driving Cars: Evaluation Of Deep Learning Techniques For Object Detection In Different Driving Conditions, Ramesh Simhambhatla, Kevin Okiah, Shravan Kuchkula, Robert Slater

SMU Data Science Review

Deep Learning has revolutionized Computer Vision, and it is the core technology behind capabilities of a self-driving car. Convolutional Neural Networks (CNNs) are at the heart of this deep learning revolution for improving the task of object detection. A number of successful object detection systems have been proposed in recent years that are based on CNNs. In this paper, an empirical evaluation of three recent meta-architectures: SSD (Single Shot multi-box Detector), R-CNN (Region-based CNN) and R-FCN (Region-based Fully Convolutional Networks) was conducted to measure how fast and accurate they are in identifying objects on the road, such as vehicles, pedestrians, …

Depressiongnn: Depression Prediction Using Graph Neural Network On Smartphone And Wearable Sensors, Param Bidja

Honors Scholar Theses

Depression prediction is a complicated classification problem because depression diagnosis involves many different social, physical, and mental signals. Traditional classification algorithms can only reach an accuracy of no more than 70% given the complexities of depression. However, a novel approach using Graph Neural Networks (GNN) can be used to reach over 80% accuracy, if a graph can represent the depression data set to capture differentiating features. Building such a graph requires 1) the definition of node features, which must be highly correlated with depression, and 2) the definition for edge metrics, which must also be highly correlated with depression. In …

Low-Energy Acceleration Of Binarized Convolutional Neural Networks Using A Spin Hall Effect Based Logic-In-Memory Architecture, Ashkan Samiee, Payal Borulkar, Ronald F. Demara, Peiyi Zhao, Yu Bai

Engineering Faculty Articles and Research

Deep Learning (DL) offers the advantages of high accuracy performance at tasks such as image recognition, learning of complex intelligent behaviors, and large-scale information retrieval problems such as intelligent web search. To attain the benefits of DL, the high computational and energy-consumption demands imposed by the underlying processing, interconnect, and memory devices on which software-based DL executes can benefit substantially from innovative hardware implementations. Logic-in-Memory (LIM) architectures offer potential approaches to attaining such throughput goals within area and energy constraints starting with the lowest layers of the hardware stack. In this paper, we develop a Spintronic Logic-in-Memory (S-LIM) XNOR neural …

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.

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 …

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 Purely Defeasible Argumentation Framework, Zimi Li

Dissertations, Theses, and Capstone Projects

Argumentation theory is concerned with the way that intelligent agents discuss whether some statement holds. It is a claim-based theory that is widely used in many areas, such as law, linguistics and computer science. In the past few years, formal argumentation frameworks have been heavily studied and applications have been proposed in fields such as natural language processing, the semantic web and multi-agent systems. Studying argumentation provides results which help in developing tools and applications in these areas. Argumentation is interesting as a logic-based approach to deal with inconsistent information. Arguments are constructed using a process like logical inference, with …

Unicorn Framework: A User-Centric Approach Toward Formal Verification Of Privacy Norms, Rezvan Joshaghani

Boise State University Theses and Dissertations

In the development of complex systems, such as user-centric privacy management systems with multiple components and attributes, it is important to formalize the process and develop mathematical models that can be utilized to automatically make decisions on the information sharing actions of users. While valuable, the current state-of-the-art models are mostly based on enterprise/organizational privacy perspectives and leave the main actor, i.e., the user, uninvolved or with limited ability to control information sharing actions. These approaches cannot be applied to a user-centric environment since user privacy policies are dynamic because they change based on the information sharing context and environment. …

Paper Prototyping Comfortable Vr Play For Diverse Sensory Needs, Louanne E. Boyd, Kendra Day, Ben Wasserman, Kaitlyn Abdo, Gillian Hayes, Erik J. Linstead

Engineering Faculty Articles and Research

We co-designed paper prototype dashboards for virtual environments for three children with diverse sensory needs. Our goal was to determine individual interaction styles in order to enable comfortable and inclusive play. As a first step towards an inclusive virtual world, we began with designing for three sensory-diverse children who have labels of neurotypical, ADHD, and autism respectively. We focused on their leisure interests and their individual sensory profiles. We present the results of co-design with family members and paper prototyping sessions conducted by family members with the children. The results contribute preliminary empirical findings for accommodating different levels of engagement …

Application-Specific Memory Subsystem Benchmarking, Mahesh Lakshminarasimhan

Boise State University Theses and Dissertations

Application performance often depends on achieved memory bandwidth. Achieved memory bandwidth varies greatly given specific combinations of instruction mix and order, working set size, and access pattern. Achieving good application performance depends on optimizing these characteristics within the constraints of the given application. This task is complicated due to the lack of information about the impact of small changes on the performance. Some information is provided by benchmarks, but most memory benchmarks are confined to simple access patterns that are not representative of patterns found in real applications.

This thesis presents AdaptMemBench, a configurable benchmark framework designed to explore the …

Public Blockchain Scalability: Advancements, Challenges And The Future, Amritraj .

Master of Science in Software Engineering Theses

In the last decade, blockchain has emerged as one of the most influential innovations in software architecture and technology. Ideally, blockchains are designed to be architecturally and politically decentralized, similar to the Internet. But recently, public and permissionless blockchains such as Bitcoin and Ethereum have faced stumbling blocks in the form of scalability. Both Bitcoin and Ethereum process fewer than 20 transactions per second, which is significantly lower than their centralized counterpart such as VISA that can process approximately 1,700 transactions per second. In realizing this hindrance in the wide range adoption of blockchains for building advanced and large scalable …

Predicting Unethical Physician Behavior At Scale: A Distributed Computing Framework, Quinn Keck, Robert Sandor, Miguel Romero, Diane Woodbridge, Paul Intrevado

Creative Activity and Research Day - CARD

As the amount of publicly shared data increases,

developing a robust pipeline to stream, store and process data is

critical, as the casual user often lacks the technology, hardware

and/or skills needed to work with such voluminous data. In

this research, the authors employ Amazon EC2 and EMR,

MongoDB, and Spark MLlib to explore 28.5 gigabytes of CMS

Open Payments data in an attempt to identify physicians who

may have a high propensity to act unethically, owing to significant

transfers of wealth from medical companies. A Random Forest

Classifier is employed to predict the top decile of physicians who

have …

Quantum Criticism, Ashwini Badgujar, Paul Intrevado, Andrew Wang, Kai Yu, David Guy Brizan

Creative Activity and Research Day - CARD

Quantum Criticism scrapes data from the News Articles and performs Sentiment Analysis.

Automated Segmentation Of Brain Ventricles Using 3d U-Net, Robert Sandor, Anish P. Dalal

Creative Activity and Research Day - CARD

Neuro-radiologists currently use qualitative volumetric change of brain ventricles after surgery to assess the safety of removing a ventriculoperitoneal (VP) shunt which is a medical device that relieves pressure on the brain caused by fluid accumulation. Following safe removal of the VP shunt, patients can be released from the hospital. The need for accurate and quick measurement of brain ventricular volumetric change makes automatic 3D segmentation software an ideal candidate to aid decisions after surgery. In this paper, we propose an approach to estimate the ventricular volume variation using segmentation in brain MRI and CT images. Our approach consists of …

An Application Of Artificial General Intelligence In Board Games, Nathan Skalka

Computer Science Graduate Research Workshop

No abstract provided.

A Grammar Based Approach To Distributed Systems Fault Diagnosis Using Log Files, Stephen Hanka

Computer Science and Engineering Theses and Dissertations

Diagnosing and correcting failures in complex, distributed systems is difficult. In a network of perhaps dozens of nodes, each of which is executing dozens of interacting applications, sometimes from different suppliers or vendors, finding the source of a system failure is a confusing, tedious piece of detective work. The person assigned this task must trace the failing command, event, or operation through the network components and find a deviation from the correct, desired interaction sequence. After a deviation is identified, the failing applications must be found, and the fault or faults traced to the incorrect source code.

Often the primary …

Bridgr: An Ios Application For Organizing And Discussing Long-Distance Carpooling, Harrison Engoren, Erik Zorn

Senior Theses

Bridgr is an iOS application that facilitates long distance carpooling. This application allows drivers to post destinations on an interactable map so that they can be linked with students that need a ride to a location within close proximity of the posted destination. The riders and driver are linked in a common chat board where they can discuss ride details among themselves. The goal of Bridgr is to allow drivers to utilize extra space in their car in turn for fellowship and/or gas money.