Digital Commons Network^™

Advancements And Challenges In Additively Manufactured Functionally Graded Materials: A Comprehensive Review, Suhas Alkunte, Ismail Fidan, Vivekanand Naikwadi, Shamil Gudavasov, Mohammad Alshaikh Ali, Mushfig Mahmudov, Seymur Hasanov, Muralimohan Cheepu

Engineering Technology Faculty Publications

This paper thoroughly examines the advancements and challenges in the field of additively manufactured Functionally Graded Materials (FGMs). It delves into conceptual approaches for FGM design, various manufacturing techniques, and the materials employed in their fabrication using additive manufacturing (AM) technologies. This paper explores the applications of FGMs in diverse fields, including structural engineering, automotive, biomedical engineering, soft robotics, electronics, 4D printing, and metamaterials. Critical issues and challenges associated with FGMs are meticulously analyzed, addressing concerns related to production and performance. Moreover, this paper forecasts future trends in FGM development, highlighting potential impacts on diverse industries. The concluding section summarizes …

Parametric Optimization Of Friction Stir Welding Of Aa6061-T6 Samples Using The Copper Donor Stir-Assisted Material Method, Aiman H. Al-Allaq, Joseph Maniscalco, Srinivasa Naik Bhukya, Zhenhua Wu, Abdelmageed Elmustafa

Mechanical & Aerospace Engineering Faculty Publications

This study presents an optimization of the process parameters for the effect of copper (Cu) donor material percentage on the friction stir welding (FSW) of AA6061-T6 alloy. Extensive factorial experiments were conducted to determine the significance of the rotational speed (ω), the transverse speed (v), the interface coefficient of friction (μ), and the Cu donor material percentage in the plunge, left, right, and downstream zones. Design Expert 13 software was used to identify the number of simulation experiments to be conducted using the Abaqus simulation software. From Design Expert 13, which is a thorough multi-objective optimization analysis software, we were …

Using Feature Selection Enhancement To Evaluate Attack Detection In The Internet Of Things Environment, Khawlah Harahsheh, Rami Al-Naimat, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The rapid evolution of technology has given rise to a connected world where billions of devices interact seamlessly, forming what is known as the Internet of Things (IoT). While the IoT offers incredible convenience and efficiency, it presents a significant challenge to cybersecurity and is characterized by various power, capacity, and computational process limitations. Machine learning techniques, particularly those encompassing supervised classification techniques, offer a systematic approach to training models using labeled datasets. These techniques enable intrusion detection systems (IDSs) to discern patterns indicative of potential attacks amidst the vast amounts of IoT data. Our investigation delves into various aspects …

Architectural Design Of A Blockchain-Enabled, Federated Learning Platform For Algorithmic Fairness In Predictive Health Care: Design Science Study, Xueping Liang, Juan Zhao, Yan Chen, Eranga Bandara, Sachin Shetty

VMASC Publications

Background: Developing effective and generalizable predictive models is critical for disease prediction and clinical decision-making, often requiring diverse samples to mitigate population bias and address algorithmic fairness. However, a major challenge is to retrieve learning models across multiple institutions without bringing in local biases and inequity, while preserving individual patients' privacy at each site.

Objective: This study aims to understand the issues of bias and fairness in the machine learning process used in the predictive health care domain. We proposed a software architecture that integrates federated learning and blockchain to improve fairness, while maintaining acceptable prediction accuracy and minimizing overhead …

Unttangling Irregular Actin Cytoskeleton Architectures In Tomograms Of The Cell With Struwwel Tracer, Salim Sazzed, Peter Scheible, Jing He, Willy Wriggers

Computer Science Faculty Publications

In this work, we established, validated, and optimized a novel computational framework for tracing arbitrarily oriented actin filaments in cryo-electron tomography maps. Our approach was designed for highly complex intracellular architectures in which a long-range cytoskeleton network extends throughout the cell bodies and protrusions. The irregular organization of the actin network, as well as cryo-electron-tomography-specific noise, missing wedge artifacts, and map dimensions call for a specialized implementation that is both robust and efficient. Our proposed solution, Struwwel Tracer, accumulates densities along paths of a specific length in various directions, starting from locally determined seed points. The highest-density paths originating …

Detecting Deceptive Dark-Pattern Web Advertisements For Blind Screen-Reader Users, Satwick Ram Kodandaram, Mohan Sunkara, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Advertisements have become commonplace on modern websites. While ads are typically designed for visual consumption, it is unclear how they affect blind users who interact with the ads using a screen reader. Existing research studies on non-visual web interaction predominantly focus on general web browsing; the specific impact of extraneous ad content on blind users' experience remains largely unexplored. To fill this gap, we conducted an interview study with 18 blind participants; we found that blind users are often deceived by ads that contextually blend in with the surrounding web page content. While ad blockers can address this problem via …

Machine-Learning-Based Vulnerability Detection And Classification In Internet Of Things Device Security, Sarah Bin Hulayyil, Shancang Li, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

Detecting cyber security vulnerabilities in the Internet of Things (IoT) devices before they are exploited is increasingly challenging and is one of the key technologies to protect IoT devices from cyber attacks. This work conducts a comprehensive survey to investigate the methods and tools used in vulnerability detection in IoT environments utilizing machine learning techniques on various datasets, i.e., IoT23. During this study, the common potential vulnerabilities of IoT architectures are analyzed on each layer and the machine learning workflow is described for detecting IoT vulnerabilities. A vulnerability detection and mitigation framework was proposed for machine learning-based vulnerability detection in …

Dental Hygiene And Dental Assistant Students' Simulated Dvi Radiographic Match Accuracy: A Pilot Study, Samantha C. Vest, Brenda T. Bradshaw, Marsha A. Voelker, Ann M. Bruhn, Tara L. Newcomb, Sinjini Sikdar

Dental Hygiene Faculty Publications

Purpose Allied dental health care professionals have served on disaster victim identification (DVI) teams; however, the literature is void of statistical measures regarding transferable skills and disaster preparedness. The purpose of this study was to assess second year dental hygiene and dental assistant students’ match accuracy for simulated DVI radiographs and compare the match accuracy between the student groups.

Methods Five patient cases were chosen at random to retrospectively collect sets of digital bitewing radiographs from two time periods. The five retrospectively selected sets of images served as simulated antemortem (AM) and postmortem (PM) radiographs. A convenience sample of second …

Model Based Systems Engineering With A Docs-As-Code Approach For The Sealion Cubesat Project, Kevin Chiu, Sean Marquez, Sharanabasaweshwara Asundi

Mechanical & Aerospace Engineering Faculty Publications

The SeaLion mission architecture team sought to create a model-based systems engineering approach to assist improving CubeSat success rates as well as for the SeaLion CubeSat project to guide an implementation for the flight software. This is important because university CubeSat teams are growing in number but often have untrained students as their core personnel. This was done using a document-as-code, or docs-as-code, approach. With this the team created tools for the systems architecture with the Mach 30 Modeling Language to create an architecture that is easy to learn and use even for newly admitted team members with little to …

Estimating Efforts For Various Activities In Agile Software Development: An Empirical Study, Lan Cao

Information Technology & Decision Sciences Faculty Publications

Effort estimation is an important practice in agile software development. The agile community believes that developers’ estimates get more accurate over time due to the cumulative effect of learning from short and frequent feedback. However, there is no empirical evidence of an improvement in estimation accuracy over time, nor have prior studies examined effort estimation in different development activities, which are associated with substantial costs. This study fills the knowledge gap in the field of software estimation in agile software development by investigating estimations across time and different development activities based on data collected from a large agile project. This …

Initial Implementation Of A Machine Learning System For Srf Cavity Fault Classification At Cebaf, A. Carpenter, K. M. Iftekharuddin, T. Powers, Y. Roblin, A. Solopava Shabalina, C. Tennant, L. Vidyaratne

Electrical & Computer Engineering Faculty Publications

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a high power Continuous Wave (CW) electron accelerator. It uses a mixture of of SRF cryomodules: older, lower energy C20/C50 modules and newer, higher energy C100 modules. The cryomodules are arrayed in two anti-parallel linear accelerators. Accurately classifying the type of cavity faults is essential to maintaining and improving accelerator performance. Each C100 cryomodule contains eight 7-cell cavities. When a cavity fault occurs within a cryomodule, all eight cavities generate 17 waveforms each containing 8192 points. This data is exported from the control system and saved for review. Analysis …

Metagomics: A Web-Based Tool For Peptide-Centric Functional And Taxonomic Analysis Of Metaproteomics Data, Michael Riffle, Damon H. May, Emma Timmins-Schiffman, Molly P. Mikan, Daniel Jaschob, William S. Noble, Brook L. Nunn

OES Faculty Publications

Metaproteomics is the characterization of all proteins being expressed by a community of organisms in a complex biological sample at a single point in time. Applications of metaproteomics range from the comparative analysis of environmental samples (such as ocean water and soil) to microbiome data from multicellular organisms (such as the human gut). Metaproteomics research is often focused on the quantitative functional makeup of the metaproteome and which organisms are making those proteins. That is: What are the functions of the currently expressed proteins? How much of the metaproteome is associated with those functions? And, which microorganisms are expressing the …

Experimental Assessment Of Mouse Sociability Using An Automated Image Processing Approach, Frency Varghese, Jessica A. Burket, Andrew D. Benson, Stephen I. Deutsch, Christian W. Zemlin

Electrical & Computer Engineering Faculty Publications

Mouse is the preferred model organism for testing drugs designed to increase sociability. We present a method to quantify mouse sociability in which the test mouse is placed in a standardized apparatus and relevant behaviors are assessed in three different sessions (called session I, II, and III). The apparatus has three compartments (see Figure 1), the left and right compartments contain an inverted cup which can house a mouse (called “stimulus mouse”). In session I, the test mouse is placed in the cage and its mobility is characterized by the number of transitions made between compartments. In session II, a …

Flexc: Protein Flexibility Prediction Using Context-Based Statistics, Predicted Structural Features, And Sequence Information, Ashraf Yaseen, Mais Nijim, Brandon Williams, Lei Qian, Min Li, Jianxin Wang, Yaohang Li

Computer Science Faculty Publications

The fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics. This flexibility of protein structures is associated with various biological processes. Predicting flexibility of residues from protein sequences is significant for analyzing the dynamic properties of proteins which will be helpful in predicting their functions.

Transverse Momentum Dependent (Tmd) Parton Distribution Functions: Status And Prospects, R. Angeles-Martinez, A. Bacchetta, I. I. Balitsky, D. Boer, M. Boglione, R. Boussarie, F. A. Ceccopieri, I. O. Cherednikov, P. Connor, M. G. Echevarria, G. Ferrera, J. Grados Luyando, F. Hautmann, H. Jung, T. Kasemets, K. Kutak, J. P. Lansberg, A. Lelek, G. Lykasov, J. D. Madrigal Martinez, P. J. Mulders, E. R. Nocera, E. Petreska, C. Pisano, R. Plaċakyte, V. Radescu, M. Radici, G. Schnell, I. Scimemi, A. Signori, L. Szymanowski, S. Taheri Monfared, F.F. Van Der Veken, H. J. Van Haevermaet, P. Van Mechelen, A. A. Vladimirov, S. Wallon

Physics Faculty Publications

We review transverse momentum dependent (TMD) parton distribution functions, their application to topical issues in high-energy physics phenomenology, and their theoretical connections with QCD resummation, evolution and factorization theorems. We illustrate the use of TMDs via examples of multi-scale problems in hadronic collisions. These include transverse momentum q_T spectra of Higgs and vector bosons for low q_T, and azimuthal correlations in the production of multiple jets associated with heavy bosons at large jet masses. We discuss computational tools for TMDs, and present the application of a new tool, TMD_LIB, to parton density fits and parameterizations.

Phylogeography Unplugged: Comparative Surveys In The Genomic Era, Brian W. Bowen, Kartik Shanker, Nina Yasuda, Maria Celia Malay, Sophie Von Der Heyden, Gustav Paulay, Luiz A. Rocha, Kimberly A. Selkoe, Paul H. Barber, Suzanne T. Williams, Harilaos A. Lessios, Eric D. Crandall, Giacomo Bernardi, Christopher P. Meyer, Kent E. Carpenter, Robert J. Toonen

Biological Sciences Faculty Publications

In March 2012, the authors met at the National Evolutionary Synthesis Center (NESCent) in Durham, North Carolina, USA, to discuss approaches and cooperative ventures in Indo-Pacific phylogeography. The group emerged with a series of findings: (1) Marine population structure is complex, but single locus mtDNA studies continue to provide powerful first assessment of phylogeographic patterns. (2) These patterns gain greater significance/power when resolved in a diversity of taxa. New analytical tools are emerging to address these analyses with multi-taxon approaches. (3) Genome-wide analyses are warranted if selection is indicated by surveys of standard markers. Such indicators can include discordance between …

Effectiveness Of A+ Learning Software In Assisting Students With Learning And Reducing Behavior Problems, Jason Buchanan

OTS Master's Level Projects & Papers

The problem of this study was to determine the effectiveness of the A+ Learning Software in assisting students with learning and reducing behavioral problems at Piedmont Alternative School.

Designing A Microcontroller Training Platform For Active Distance Learning Engineering And Technology Students, Steve C. Hsiung, James E. Eiland, John R. Hackworth, John Ritz

Engineering Technology Faculty Publications

This is an active distance-learning project that addresses the hands-on microprocessor/ mi-crocontroller-related courses. A research team designed a low-cost training system with supporting instructional materials to assist the teaching of these concepts. Individual laboratory activities are being developed to reinforce student learning and skill development in programming concepts. This basic system format eventually will support an array of engineering and technology courses. This project involves two community colleges, Blue Ridge Community College (BRCC) and Olympic College (OC), and a four-year university, Old Dominion University (ODU), in a collaborative research team to design and develop a specific PIC microcontroller training system …

Ivr Test & Survey: A Computer Program To Collect Data Via Computerized Telephonic Applications, Louis H. Janda, Michael Janda, Eric Tedford

Psychology Faculty Publications

Several studies have demonstrated the advantages of using interactive voice response (IVR) technology to collect self-report data from research participants and recipients of psychological/medical services. IVR allows participants to phone a computer and respond to recorded questions by pressing the appropriate touch-tone keys on their telephone. Because this technology offers substantial benefits in terms of cost and efficiency, it is surprising that it has not been more widely utilized by researchers and practitioners. Along with the automation of the administration and scoring of tests or surveys, IVR provides for questioning to be adapted to the participants' responses. One possible explanation …

Reviewing Software As A Means Of Enhancing Instruction, Marcus D. Childress, Guang-Lea Lee, Gregory P. Sherman

Teaching & Learning Faculty Publications

A software review procedure developed by the authors is described. The procedure centers around a form that extends the functionality of traditional software evaluation forms by enhancing the use of the computer software in the early childhood classroom. The form encourages teachers to discover ways a piece of software can be integrated across disciplines and used as an anchor for instruction. Users of the review form are also encouraged to examine ways the software motivates the user to remain engaged in its use. The majority of the review form emphasizes the important role of the teacher in identifying outcomes or …