Other Computer Sciences Commons^™

A Deep Learning-Based Approach To Extraction Of Filler Morphology In Sem Images With The Application Of Automated Quality Inspection, Md. Fashiar Rahman, Tzu-Liang Bill Tseng, Jianguo Wu, Yuxin Wen, Yirong Lin

Engineering Faculty Articles and Research

Automatic extraction of filler morphology (size, orientation, and spatial distribution) in Scanning Electron Microscopic (SEM) images is essential in many applications such as automatic quality inspection in composite manufacturing. Extraction of filler morphology greatly depends on accurate segmentation of fillers (fibers and particles), which is a challenging task due to the overlap of fibers and particles and their obscure presence in SEM images. Convolution Neural Networks (CNNs) have been shown to be very effective at object recognition in digital images. This paper proposes an automatic filler detection system in SEM images, utilizing a Mask Region-based CNN architecture. The proposed system …

A High Precision Machine Learning-Enabled System For Predicting Idiopathic Ventricular Arrhythmia Origins, Jianwei Zheng, Guohua Fu, Daniele Struppa, Islam Abudayyeh, Tahmeed Contractor, Kyle Anderson, Huimin Chu, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Background: Radiofrequency catheter ablation (CA) is an efficient antiarrhythmic treatment with a class I indication for idiopathic ventricular arrhythmia (IVA), only when drugs are ineffective or have unacceptable side effects. The accurate prediction of the origins of IVA can significantly increase the operation success rate, reduce operation duration and decrease the risk of complications. The present work proposes an artificial intelligence-enabled ECG analysis algorithm to estimate possible origins of idiopathic ventricular arrhythmia at a clinical-grade level accuracy.

Method: A total of 18,612 ECG recordings extracted from 545 patients who underwent successful CA to treat IVA were proportionally sampled into training, …

Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison

Engineering Faculty Articles and Research

Vast improvements in communications technology are possible if the conversion of digital information from optical to electric and back can be removed. Plasmonic devices offer one solution due to optical computing’s potential for increased bandwidth, which would enable increased throughput and enhanced security. Plasmonic devices have small footprints and interface with electronics easily, but these potential improvements are offset by the large device footprints of conventional signal regeneration schemes, since surface plasmon polaritons (SPPs) are incredibly lossy. As such, there is a need for novel regeneration schemes. The continuous, uniform, and unambiguous digital information encoding method is phase-shift-keying (PSK), so …

Multi-Dimensional Security Integrity Analysis Of Broad Market Internet-Connected Cameras, Mark A. Stanislav

Masters Theses & Doctoral Dissertations

This study used a quantitative approach with a cross-sectional, descriptive analysis survey design to examine the adherence of 40 internet-connected cameras against three IoT security frameworks to determine their overall security posture. Relevant literature was reviewed showing that prior studies in a similar regard had limitations, such as a small sample population, singular market segment focus, and/or a lack of validation against formalized frameworks. This study resulted in a uniform and multi-dimensional set of findings with supporting evidence, leading to a mapping against selected IoT security frameworks that was then quantitatively analyzed for their relative adherence as individual cameras, across …

Improving Adversarial Attacks Against Malconv, Justin Burr

Masters Theses & Doctoral Dissertations

This dissertation proposes several improvements to existing adversarial attacks against MalConv, a raw-byte malware classifier for Windows PE files. The included contributions greatly improve the success rates and performance of gradient-based file overlay attacks. All improvements are included in a new open-source attack utility called BitCamo.

Several new payload initialization strategies for use with gradient-based attacks are proposed and evaluated as potential replacements for the randomized initialization method used by current attacks. An algorithm for determining the optimal payload size is also proposed. The resulting improvements achieve a 100% evasion rate against eligible target executables using an average payload size …

Patterns Of Academic Help-Seeking In Undergraduate Computing Students, Augie Doebling

Master's Theses

Knowing when and how to seek academic help is crucial to the success of undergraduate computing students. While individual help-seeking resources have been studied, little is understood about the factors influencing students to use or avoid certain re- sources. Understanding students’ patterns of help-seeking can help identify factors contributing to utilization or avoidance of help resources by different groups, an important step toward improving the quality and accessibility of resources. We present a mixed-methods study investigating the help-seeking behavior of undergraduate computing students. We collected survey data (n = 138) about students’ frequency of using several resources followed by one-on-one …

Socioapp: Detecting Your Sociability Status With Your Smartphone, Aaron Walker

Research in the Capitol

Loneliness, isolation, and anti-social behaviors have increased in the past few years, whether that be due to social media, people paying more attention to their devices, or due to the COVID-19 pandemic. These behaviors are proven to decrease a student’s academic performance, causing their grades to decline, and disabling their motivation to learn. We aim to gain insight on this issue via the application of smartphone technology and machine learning, enabling those that use our app to understand if their being social or anti-social. We use a variety of sensors, location devices, and speaker recognition algorithms to identify behaviors that …

The Effect Of Using The Gamification Strategy On Academic Achievement And Motivation Towards Learning Problem-Solving Skills In Computer And Information Technology Course Among Tenth Grade Female Students, Mazyunah Almutairi, Prof. Ahmad Almassaad

International Journal for Research in Education

Abstract

This study aimed to identify the effect of using the gamification strategy on academic achievement and motivation towards learning problem-solving skills in computer and information technology course. A quasi-experimental method was adopted. The study population included tenth-grade female students in Al-Badi’ah schools in Riyadh. The sample consisted of 54 students divided into two equal groups: control group and experimental group. The study tools comprised an achievement test and the motivation scale. The results showed that there were statistically significant differences between the two groups in the academic achievement test in favor of the experimental group, with a large effect …

Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead

Engineering Faculty Articles and Research

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of …

Bridges And Barriers: An Exploration Of Engagements Of The Research Community With The Openstreetmap Community, A. Yair Grinberger, Marco Minghini, Godwin Yeboah, Levente Juhasz, Peter Mooney

GIS Center

The academic community frequently engages with OpenStreetMap (OSM) as a data source and research subject, acknowledging its complex and contextual nature. However, existing literature rarely considers the position of academic research in relation to the OSM community. In this paper we explore the extent and nature of engagement between the academic research community and the larger communities in OSM. An analysis of OSM-related publications from 2016 to 2019 and seven interviews conducted with members of one research group engaged in OSM-related research are described. The literature analysis seeks to uncover general engagement patterns while the interviews are used to identify …

Microsoft Defender Will Be Defended: Memoryranger Prevents Blinding Windows Av, Denis Pogonin, Igor Korkin, Phd

Annual ADFSL Conference on Digital Forensics, Security and Law

Windows OS is facing a huge rise in kernel attacks. An overview of popular techniques that result in loading kernel drivers will be presented. One of the key targets of modern threats is disabling and blinding Microsoft Defender, a default Windows AV. The analysis of recent driver-based attacks will be given, the challenge is to block them. The survey of user- and kernel-level attacks on Microsoft Defender will be given. One of the recently published attackers’ techniques abuses Mandatory Integrity Control (MIC) and Security Reference Monitor (SRM) by modifying Integrity Level and Debug Privileges for the Microsoft Defender via syscalls. …

Marine Fishery Management Agent-Based Modeling, Hiroki Sato

Honors Program Theses

Fisheries in the United States not only provide seafood for us to enjoy and contribute significantly to the American economy, they also help us to sustain ecological balance and protect our ocean resources. Fishery management agencies in the United States conduct stock assessments to discover the changes in the abundance of fishery stocks in response to changes in the environment and effects of commercial and recreational fishing. Efficient stock assessment enables maintenance of healthy fisheries without permanently damaging the marine ecosystem. In order to forecast the future trend of fisheries, predicting fish migration patterns in response to the environmental factors …

Data Science Applied To Discover Ancient Minoan-Indus Valley Trade Routes Implied By Commonweight Measures, Peter Revesz

CSE Conference and Workshop Papers

This paper applies data mining of weight measures to discover possible long-distance trade routes among Bronze Age civilizations from the Mediterranean area to India. As a result, a new northern route via the Black Sea is discovered between the Minoan and the Indus Valley civilizations. This discovery enhances the growing set of evidence for a strong and vibrant connection among Bronze Age civilizations.

Sustainable Computing - Without The Hot Air, Noman Bashir, David Irwin, Prashant Shenoy, Abel Souza

Publications

The demand for computing is continuing to grow exponentially. This growth will translate to exponential growth in computing's energy consumption unless improvements in its energy-efficiency can outpace increases in its demand. Yet, after decades of research, further improving energy-efficiency is becoming increasingly challenging, as it is already highly optimized. As a result, at some point, increases in computing demand are likely to outpace increases in its energy-efficiency, potentially by a wide margin. Such exponential growth, if left unchecked, will position computing as a substantial contributor to global carbon emissions. While prominent technology companies have recognized the problem and sought to …

Model-Based Testing Of Smart Home Systems Using Efsm, Cefsm, And Fsmapp, Afnan Mohammed Albahli

Electronic Theses and Dissertations

Smart Home Systems (SHS) are some of the most popular Internet of Things (IoT) applications. In 2021, there were 52.22 million smart homes in the United States and they are expected to grow to 77.1 million in 2025 [71]. According to MediaPost [74], 69 percent of American households have at least one smart home device. The number of smart home systems poses a challenge for software testers to find the right approach to test these systems. This dissertation employs Extended Finite State Machines (EFSMs) [6, 24, 105], Communicating Extended Finite State Machines (EFSMs) [68] and FSMApp [10] to generate reusable …

Human-Controlled Fuzzing With Afl, Maxim Grishin, Igor Korkin, Phd

Annual ADFSL Conference on Digital Forensics, Security and Law

Fuzzing techniques are applied to reveal different types of bugs and vulnerabilities. American Fuzzy Lop (AFL) is a free most popular software fuzzer used by many other fuzzing frameworks. AFL supports autonomous mode of operation that uses the previous step output into the next step, as a result fuzzer spends a lot of time analyzing minor code sections. By making fuzzing process more focused and human controlled security expert can save time and find more bugs in less time. We designed a new module that can fuzz only the specified functions. As a result, the chosen ones will be inspected …

Odu Undergraduate Students Addressing The Societal Problems Of Parking Control, Classroom Seating, And Flood Monitoring In Hampton Roads, Stephanie K. Trusty, Gabriel Del Razo, Nathan Potter, Soad Ibrahim, Ayman Elmesalami

OUR Journal: ODU Undergraduate Research Journal

During the summer of 2021, ODU undergraduate computer science students undertook image processing research projects. These projects focused on utilizing the Raspberry Pi computer and camera module to address three real-world problems concerning parking control, classroom seating, and flood monitoring. The parking lot occupancy project aimed to develop a system that monitors the occupancy of parking spaces in a lot and communicates the status of the lot of drivers and the lot attendants. The COVID-19 classroom occupancy project sought to enforce social distancing protocols in a classroom environment by detecting seating violations and notifying the instructor and the impacted students …

The Amorphous Nature Of Hackers: An Exploratory Study, Kento Yasuhara, Daniel Walnycky, Ibrahim Baggili, Ahmed Alhishwan

Annual ADFSL Conference on Digital Forensics, Security and Law

In this work, we aim to better understand outsider perspectives of the hacker community through a series of situation based survey questions. By doing this, we hope to gain insight into the overall reputation of hackers from participants in a wide range of technical and non-technical backgrounds. This is important to digital forensics since convicted hackers will be tried by people, each with their own perception of who hackers are. Do cyber crimes and national security issues negatively affect people’s perceptions of hackers? Does hacktivism and information warfare positively affect people’s perception of hackers? Do individual personality factors affect one’s …

Timestamp Estimation From Outdoor Scenes, Tawfiq Salem, Jisoo Hwang, Rafael Padilha

Annual ADFSL Conference on Digital Forensics, Security and Law

The increasing availability of smartphones allowed people to easily capture and share images on the internet. These images are often associated with metadata, including the image capture time (timestamp) and the location where the image was captured (geolocation). The metadata associated with images provides valuable information to better understand scenes and events presented in these images. The timestamp can be manipulated intentionally to provide false information to convey a twisted version of reality. Images with manipulated timestamps are often used as a cover-up for wrongdoing or broadcasting false claims and competing views on the internet. Estimating the time of capture …

Detection Of Overlapping Passive Manipulation Techniques In Image Forensics, Gianna S. Lint, Umit Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

With a growing number of images uploaded daily to social media sites, it is essential to understand if an image can be used to trace its origin. Forensic investigations are focusing on analyzing images that are uploaded to social media sites resulting in an emphasis on building and validating tools. There has been a strong focus on understanding active manipulation or tampering techniques and building tools for analysis. However, research on manipulation is often studied in a vacuum, involving only one technique at a time. Additionally, less focus has been placed on passive manipulation, which can occur by simply uploading …