Other Computer Engineering Commons^™

Using Deep Neural Network And Transformers To Extract Graphene Compounds And Properties, Ayman Ibn Jaman

Computer Science Graduate Research Workshop

No abstract provided.

Mapping Renewal: How An Unexpected Interdisciplinary Collaboration Transformed A Digital Humanities Project, Elise Tanner, Geoffrey Joseph

Digital Initiatives Symposium

Funded by a National Endowment for Humanities (NEH) Humanities Collections and Reference Resources Foundations Grant, the UA Little Rock Center for Arkansas History and Culture’s “Mapping Renewal” pilot project focused on creating access to and providing spatial context to archival materials related to racial segregation and urban renewal in the city of Little Rock, Arkansas, from 1954-1989. An unplanned interdisciplinary collaboration with the UA Little Rock Arkansas Economic Development Institute (AEDI) has proven to be an invaluable partnership. One team member from each department will demonstrate the Mapping Renewal website and discuss how the collaborative process has changed and shaped …

Infiltrating Cloud Storage Of Iot Devices Using Ransomware, Anna Millerhagen

Ramaley Celebration

Infiltrating Cloud Storage of IoT devices using Ransomware

Anna Millerhagen

Computer science Department

Advisor: Eric Wright

Security is necessary for all areas of computer science. The expanding world of IT is IoT devices. There are many smart devices in our daily lives such as smart speakers, smart light bulbs, smart watches, doorbell cams, security systems, smart smoke alarms, smart cars, and many more. The need for security in these devices is critical. Any one of these devices could be the weak link to a security breach. These devices are all enabled and communicate through cloud services. They interact with various …

Investigating Dataset Distinctiveness, Andrew Ulmer, Kent W. Gauen, Yung-Hsiang Lu, Zohar R. Kapach, Daniel P. Merrick

The Summer Undergraduate Research Fellowship (SURF) Symposium

Just as a human might struggle to interpret another human’s handwriting, a computer vision program might fail when asked to perform one task in two different domains. To be more specific, visualize a self-driving car as a human driver who had only ever driven on clear, sunny days, during daylight hours. This driver – the self-driving car – would inevitably face a significant challenge when asked to drive when it is violently raining or foggy during the night, putting the safety of its passengers in danger. An extensive understanding of the data we use to teach computer vision models – …

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.

Cusigns: A Dynamic Solution For Digital Signage, Jonathan Easterday, Wesley Kelly, Todd Landis, Nicole D. Perez

The Research and Scholarship Symposium (2013-2019)

Cedarville University has computer monitors located throughout campus in order to show advertisements and important information to students, faculty, and staff. The slides shown on these displays are scheduled using Concerto: web-based software which manages digital signage. Though the Concerto software is currently used to manage digital signage, Cedarville University’s IT department desires features which Concerto does not provide, including the ability to play videos, a better slide randomization algorithm, emergency broadcasting features, and an intuitive user interface. We have created a new solution for digital signage called CUSigns with the goal of providing the existing functionality of Concerto while …

Two Correspondence Problems Easier Than One, Aaron Michaux, Zygmunt Pizlo

MODVIS Workshop

Computer vision research rarely makes use of symmetry in stereo reconstruction despite its established importance in perceptual psychology. Such stereo reconstructions produce visually satisfying figures with precisely located points and lines, even when input images have low or moderate resolution. However, because few invariants exist, there are no known general approaches to solving symmetry correspondence on real images. The problem is significantly easier when combined with the binocular correspondence problem, because each correspondence problem provides strong non-overlapping constraints on the solution space. We demonstrate a system that leverages these constraints to produce accurate stereo models from pairs of binocular images …

Is Real-Time Mobile Content-Based Image Retrieval Feasible?, Colin G. Graber, Anup Mohan, Yung-Hsiang Lu

The Summer Undergraduate Research Fellowship (SURF) Symposium

Content-based image retrieval (CBIR) is a method of searching through a database of images by using another image as a query instead of text. Recent advances in the processing power of smart phones and tablets, collectively known as mobile devices, have prompted researchers to attempt to construct mobile CBIR systems. Most of the research that has been conducted on mobile CBIR has focused on improving either its accuracy or its run-time, but not both simultaneously. We set out to answer the question: is real-time CBIR with manageable accuracy possible on current mobile devices? To find the answer to this question, …