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Full-Text Articles in Physical Sciences and Mathematics

Augmented Reality Headset Facilitates Exposure For Surgical Stabilization Of Rib Fractures, T. Sensing, Pratik Parikh, Claire Hardman, Thomas Wischgoll, Sadan Suneesh Menon Jan 2021

Augmented Reality Headset Facilitates Exposure For Surgical Stabilization Of Rib Fractures, T. Sensing, Pratik Parikh, Claire Hardman, Thomas Wischgoll, Sadan Suneesh Menon

Computer Science and Engineering Faculty Publications

Recent advances in augmented reality (AR) technology have made it more accessible, portable, and powerful. AR headsets differentiate themselves from virtual reality in that they allow the wearer an unobstructed view of the “real world” but with an image superimposed upon it. The technology has many potential applications in medicine, including surgical planning, simulation, and medical education. The aim of this project was to provide proof of concept that using an AR headset during surgical stabilization of rib fractures (SSRF) is feasible. We theorized that the use of AR could allow for more precise localization of fractures, allowing for smaller ...


Endangered Bat Conservation In Wsu Woods, Olivia Norris, Josh Miller, Mitchell Link, Molly Nelson, Susan Fike Dec 2020

Endangered Bat Conservation In Wsu Woods, Olivia Norris, Josh Miller, Mitchell Link, Molly Nelson, Susan Fike

Runkle Woods Symposia

Our project focused on two endangered bat species in the Wright State Woods, the Indiana Bat and the Little Brown Bat. Our presentation covers topics such as general info, social behaviors, current threats, bat boxes, and conservation methods and goals.


Wright State Prairie Expansion, Kailani Sparrow, Reynold Kojo Papa Afful Ephraim Dec 2020

Wright State Prairie Expansion, Kailani Sparrow, Reynold Kojo Papa Afful Ephraim

Runkle Woods Symposia

Our plan is to convert the northern edge of Wright State Woods along Kaufman Ave. into a prairie to provide a habitat for pollinator species that are declining due to habitat loss and other factors and to provide a scenic and educational area


Your Mom Isn’T Here To Pick Up After You… In Your Dorm Or On The Rest Of Campus, Madison Glass, Jonathan Hume, Mckenzie Stefanoff, Brandon Butler Dec 2020

Your Mom Isn’T Here To Pick Up After You… In Your Dorm Or On The Rest Of Campus, Madison Glass, Jonathan Hume, Mckenzie Stefanoff, Brandon Butler

Runkle Woods Symposia

Research and the litter that plagues the Wright State University Woods and what we can do about it as a campus community.


Multi-Echo Quantitative Susceptibility Mapping For Strategically Acquired Gradient Echo (Stage) Imaging, Sara Gharabaghi, Saifeng Liu, Ying Wang, Yongsheng Chen, Sagar Buch, Mojtaba Jokar, Thomas Wischgoll, Nasser H. Kashou, Chunyan Zhang, Bo Wu, Jingliang Cheng, E. Mark Haacke Oct 2020

Multi-Echo Quantitative Susceptibility Mapping For Strategically Acquired Gradient Echo (Stage) Imaging, Sara Gharabaghi, Saifeng Liu, Ying Wang, Yongsheng Chen, Sagar Buch, Mojtaba Jokar, Thomas Wischgoll, Nasser H. Kashou, Chunyan Zhang, Bo Wu, Jingliang Cheng, E. Mark Haacke

Computer Science and Engineering Faculty Publications

Purpose: To develop a method to reconstruct quantitative susceptibility mapping (QSM) from multi-echo, multi-flip angle data collected using strategically acquired gradient echo (STAGE) imaging. Methods: The proposed QSM reconstruction algorithm, referred to as “structurally constrained Susceptibility Weighted Imaging and Mapping” scSWIM, performs an ℓ1 and ℓ2 regularization-based reconstruction in a single step. The unique contrast of the T1 weighted enhanced (T1WE) image derived from STAGE imaging was used to extract reliable geometry constraints to protect the basal ganglia from over-smoothing. The multi-echo multi-flip angle data were used for improving the contrast-to-noise ratio in QSM through a weighted averaging scheme. The ...


Assessment Of Soil Properties Under Different Land Use Types In Olokemeji Forest Reserves In Ogun State Southwestern Nigeria, Oluwatoyin Opeyemi Akintola, Adewunmi Idayat Bodede, Michael Smart, Ayodeji Gideon Adebayo, Olawale Nurean Sulaiman Sep 2020

Assessment Of Soil Properties Under Different Land Use Types In Olokemeji Forest Reserves In Ogun State Southwestern Nigeria, Oluwatoyin Opeyemi Akintola, Adewunmi Idayat Bodede, Michael Smart, Ayodeji Gideon Adebayo, Olawale Nurean Sulaiman

Journal of Bioresource Management

Knowledge of soil properties is essential for environmental sustainability for any forest reserve or plantation. The physical and chemical properties of soil under three different land uses was investigated to assess the nutrient and fertility status of the soils. Fifteen soil samples, each collected from different locations within the natural forest, plantation and farm land were analyzed for soil texture, bulk density, porosity, pH, organic carbon, organic matter content, total nitrogen, available phosphorus, Na, K, Ca, Mg, Zn, Cu, Fe and Mn. Texturally, the soils were loamy, loamy sand and sandy loamy in the natural forest, plantation and farmland respectively ...


Prediction Of Feed Utilization Performance In Clarias Gariepinus Using Multiple Linear Regression In Machine Learning, Adekunle Oluwatosin Familusi Jun 2020

Prediction Of Feed Utilization Performance In Clarias Gariepinus Using Multiple Linear Regression In Machine Learning, Adekunle Oluwatosin Familusi

Journal of Bioresource Management

Machine learning models can be used to make predictions about nutrient utilization performance index using available proximate analysis data on feed composition. Data from similar experiments on nutrient utilization performance was used to fit a multiple linear regression model for the prediction of four performance indexes. The Specific Growth Rate and percentage inclusion with strength of 0.57 was noted along with a negative relationship between protein efficiency and protein content. A negative relationship between Nitrogen Free Extract (NFE) and Protein Efficiency Ratio (PER) at NFE content ≥25 % was observed. PER was predicted with 85 % accuracy, while Weight Gain (WG ...


Physical And Chemical Properties Of Soils In Gambari Forest Reserve Near Ibadan, South Western Nigeria., Akintola O. Opeyemi Dr, Bodede Idayat Adewunmi Dr, Abiola Isaac Oluwaseyi Dr Jun 2020

Physical And Chemical Properties Of Soils In Gambari Forest Reserve Near Ibadan, South Western Nigeria., Akintola O. Opeyemi Dr, Bodede Idayat Adewunmi Dr, Abiola Isaac Oluwaseyi Dr

Journal of Bioresource Management

The different features of soil greatly affect the flora and vegetative diversity of a forest. The physical and chemical characteristics of soils in Onigambari Forest Reserve were evaluated to assess the fertility and productivity status of the soils. Fifteen soil samples collected from different sample locations were analyzed for soil texture (sand, silt and clay), bulk density, porosity, pH, organic matter, total nitrogen, available phosphorus, exchangeable bases (Na, K, Ca and Mg) and available micronutrients (Zn, Cu, Fe and Mn). Texturally, the studied soils were loamy sand and sandy loam with percentage of sands (71.2-84.2 %), silts (7.4-10 ...


Measuring Nomophobia And Exploration Of Consequences And Comorbidities, Sarah Marie Fryman, William L. Romine Apr 2020

Measuring Nomophobia And Exploration Of Consequences And Comorbidities, Sarah Marie Fryman, William L. Romine

Symposium of Student Research, Scholarship, and Creative Activities Materials

Excessive use of smartphones has coined the term “Nomophobia”, or fear of not being able to use your smartphone. For many, these devices have become an extension of ourselves, which raises hesitation on whether or not society has become addicted to smartphones. Specific diagnostic criteria for smartphone addiction have yet to be settled, and even appropriate to use the word “addiction” when describing excessive usage of smartphones is controversial.

We therefore explore utilize current measures to explore the symptoms of nomophobia and their hierarchy, as well as comorbidities including social anxiety, self-esteem, distracted driving and sleep quality. A total of ...


The Wright State – Lake Campus 2019 – 2020 Scholarly Review, Wright State University - Lake Campus Apr 2020

The Wright State – Lake Campus 2019 – 2020 Scholarly Review, Wright State University - Lake Campus

Lake Campus Research Symposium Reports

This report provides a listing of the scholarly endeavors from Lake Campus during the 2018 calendar year spanning across disciplines.

This document contains the Annual Research Report from 2019 and the Research Symposium Program from 2020.


Potential For Wetlands To Remediate Harmful Pathogenic Fecal Coliform Bacteria From Streams, C. Ewing, Benjamin Strang, Bradley Axe, Jocelyn Birt, Brayden Kinney, Zachary Senger, Stephen J. Jacquemin Apr 2020

Potential For Wetlands To Remediate Harmful Pathogenic Fecal Coliform Bacteria From Streams, C. Ewing, Benjamin Strang, Bradley Axe, Jocelyn Birt, Brayden Kinney, Zachary Senger, Stephen J. Jacquemin

Lake Campus Research Symposium Abstracts and Posters

Wetlands are increasingly becoming a cornerstone of stream remediation in the highly eutrophic regions of the Midwestern United States. Wetlands have numerous advantages over other technologies as they incorporate natural biological process resultant from plants and bacteria while also providing an increase in wildlife habitat and greenspaces rather than relying on costly and technologically complex processes to treat waterways. The capacity for wetlands to remediate nutrients and improve water clarity is fairly well established. However, less is known about their potential to affect changes in the pathogenic microbial communities (such as E. coli) commonly associated with runoff in agricultural areas ...


Snakes On A Plain: Paleontology, Archeology, And History Of The Rattlesnake And Garter Snake In Western Ohio, Ryan Shell, David Peterman, Charles Ciampaglio, Stephen J. Jacquemin Apr 2020

Snakes On A Plain: Paleontology, Archeology, And History Of The Rattlesnake And Garter Snake In Western Ohio, Ryan Shell, David Peterman, Charles Ciampaglio, Stephen J. Jacquemin

Lake Campus Research Symposium Abstracts and Posters

During an investigation of caves in Taylorsville Metropark, near Dayton, Ohio, vertebral remains of rattlesnake (Crotalus sp.) and garter snake (Thamnophis sp.) were recovered from sites radiocarbon dated to a the historical period (~146 years before present) and to the Hopewell Archeological period (~1,433 years before present). The latter specimens recovered represent the some of the oldest sub-fossil evidence of the migration of these genera into the plains and forests of Ohio. A review of scientific and historical records for each genus indicates thatThamnophis appeared in the region prior to the end of the Pleistocene Epoch and persisted in ...


Continuous Water Quality Monitoring Platform For Grand Lake St Marys, Aaron Neikamp, Alex Lehman, Brandon Siefring, Jason Evers, Ryan M. Spicer, Shayna R. Petitjean Apr 2020

Continuous Water Quality Monitoring Platform For Grand Lake St Marys, Aaron Neikamp, Alex Lehman, Brandon Siefring, Jason Evers, Ryan M. Spicer, Shayna R. Petitjean

Lake Campus Research Symposium Abstracts and Posters

For the past decade, Grand Lake St. Marys (GLSM) has struggled to provide a stable and clean water source for the community affecting people and businesses alike. A safe level of microcystin –a toxin in the harmful algal blooms–is 20 ppb in recreational water, and GLSM has seen an excess of 82 ppb. As of now, there is no solution to continuously monitor the water quality; therefore, corrective actions are only based off intermittent samples taken by hand. A solution to this issue would be a water quality platform (WQP) that monitors parameters such as water and air temperature ...


Multi-Label Model For Toxicity Prediction, Xiu Huan Yap, Michael L. Raymer Apr 2020

Multi-Label Model For Toxicity Prediction, Xiu Huan Yap, Michael L. Raymer

Symposium of Student Research, Scholarship, and Creative Activities Materials

Most computational predictive models are specifically trained for a single toxicity endpoint. Since more than 1300 toxicity assays have been reported in the TOXCAST dashboard, achieving high coverage over this growing number of toxicity endpoints remains challenging. Furthermore, single-endpoint models lack the ability to learn dependencies between endpoints, such as those targeting similar biological pathways, which may be used to boost model performance. In this study, we characterize the performance of 3 multi-label classification (MLC) models, namely Classifier Chains (CC), Label Powersets (LP) and Stacking (SBR), on Tox21 challenge data. These MLC models employ the Problem Transformation approach, which is ...


Describing Quasi-Graphic Matroids, Nathan Bowler, Daryl Funk, Dan Slilaty Mar 2020

Describing Quasi-Graphic Matroids, Nathan Bowler, Daryl Funk, Dan Slilaty

Mathematics and Statistics Faculty Publications

The class of quasi-graphic matroids recently introduced by Geelen, Gerards, and Whittle generalises each of the classes of frame matroids and liftedgraphic matroids introduced earlier by Zaslavsky. For each biased graph (G, B) Zaslavsky defined a unique lift matroid L(G, B) and a unique frame matroid F(G, B), each on ground set E(G). We show that in general there may be many quasi-graphic matroids on E(G) and describe them all: for each graph G and partition (B, L, F) of its cycles such that B satisfies the theta property and each cycle in L meets each ...


Finding Pythagoras In The Pythagoreans, Brandon Barnes Jan 2020

Finding Pythagoras In The Pythagoreans, Brandon Barnes

Classics Ancient Science Fair

This presentation for the Ancient Science Fair deals with the Pythagorean Theorem. Since Pythagoras himself did not write down his work, early scholars had to work to find the knowledge and unify it among differing sources.


Medical Education And Assisted Surgery By Ar, Sadan Suneesh Menon, Thomas Wischgoll, Sharon Farra, Cindra Holland Jan 2020

Medical Education And Assisted Surgery By Ar, Sadan Suneesh Menon, Thomas Wischgoll, Sharon Farra, Cindra Holland

Computer Science and Engineering Faculty Publications

No abstract provided.


Uncertainty-Aware Brain Lesion Visualization, Christina Gillmann, Dorothee Saur, Thomas Wischgoll, Karl T. Hoffman, Hans Hagen, Ross Maciejewski, Gerik Scheuermann Jan 2020

Uncertainty-Aware Brain Lesion Visualization, Christina Gillmann, Dorothee Saur, Thomas Wischgoll, Karl T. Hoffman, Hans Hagen, Ross Maciejewski, Gerik Scheuermann

Computer Science and Engineering Faculty Publications

A brain lesion is an area of tissue that has been damaged through injury or disease. Its analysis is an essential task for medical researchers to understand diseases and find proper treatments. In this context, visualization approaches became an important tool to locate, quantify, and analyze brain lesions. Unfortunately, image uncertainty highly effects the accuracy of the visualization output. These effects are not covered well in existing approaches, leading to miss-interpretation or a lack of trust in the analysis result. In this work, we present an uncertainty-aware visualization pipeline especially designed forbrain lesions. Our method is based on an uncertainty ...


Extracting Information From Subroutines Using Static Analysis Semantics, Luke A. Burnett Jan 2020

Extracting Information From Subroutines Using Static Analysis Semantics, Luke A. Burnett

Browse all Theses and Dissertations

Understanding how a system component can interact with other services can take an immeasurable amount of time. Reverse engineering embedded and large systems can rely on understanding how components interact with one another. This process is time consuming and can sometimes be generalized through certain behavior.We will be explaining two such complicated systems and highlighting similarities between them. We will show that through static analysis you can capture compiler behavior and apply it to the understanding of a function, reducing the total time required to understand a component of whichever system you are learning.


Topological Analysis Of Averaged Sentence Embeddings, Wesley J. Holmes Jan 2020

Topological Analysis Of Averaged Sentence Embeddings, Wesley J. Holmes

Browse all Theses and Dissertations

Sentence embeddings are frequently generated by using complex, pretrained models that were trained on a very general corpus of data. This thesis explores a potential alternative method for generating high-quality sentence embeddings for highly specialized corpora in an efficient manner. A framework for visualizing and analyzing sentence embeddings is developed to help assess the quality of sentence embeddings for a highly specialized corpus of documents related to the 2019 coronavirus epidemic. A Topological Data Analysis (TDA) technique is explored as an alternative method for grouping embeddings for document clustering and topic modeling tasks and is compared to a simple clustering ...


Development Of Real-Time Systems For Supporting Collaborations In Distributed Human And Machine Teams, Aishwarya Bositty Jan 2020

Development Of Real-Time Systems For Supporting Collaborations In Distributed Human And Machine Teams, Aishwarya Bositty

Browse all Theses and Dissertations

Real-time distributed systems constitute computing nodes that are connected by a network and coordinate with one another to accomplish a cooperative task, combining the responsiveness, fault-tolerance and geographic independence to support time-constrained collaborative applications, including distributed Human-Machine Teaming. In this thesis research the viability of real-time distributed collaborative technologies is demonstrated through the design, development and validation of prototype systems that support two human-machine teaming scenarios namely, ACE-IMS (Affirmation Cue based Interruption Management Systems) and ReadMI (Real-time Assessment of Dialogue in Motivational Interview). ACE-IMS demonstrates how a combination of AI capabilities and the cloud and mobile computing infrastructure can be ...


Hierarchical Anomaly Detection For Time Series Data, Ryan E. Sperl Jan 2020

Hierarchical Anomaly Detection For Time Series Data, Ryan E. Sperl

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With the rise of Big Data and the Internet of Things, there is an increasing availability of large volumes of real-time streaming data. Unusual occurrences in the underlying system will be reflected in these streams, but any human analysis will quickly become out of date. There is a need for automatic analysis of streaming data capable of identifying these anomalous behaviors as they occur, to give ample time to react. In order to handle many high-velocity data streams, detectors must minimize the processing requirements per value. In this thesis, we have developed a novel anomaly detection method which makes use ...


Investigating Heterogeneous Nucleation Of Barite Using Hydrothermal Atomic Force Microscopy And Optical Microscopy, Ankita B. Gurav Jan 2020

Investigating Heterogeneous Nucleation Of Barite Using Hydrothermal Atomic Force Microscopy And Optical Microscopy, Ankita B. Gurav

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In order to develop a better understanding heterogeneous nucleation of barite, barite precipitation was studied under varying experimental parameters. Hydrothermal atomic force microscopy (HAFM) and optical microscopy were used to investigate the effect of change in temperature, supersaturation and varying ratios of ions on heterogeneous nucleation of barite. In the experiments conducted at higher temperatures, the particles thus nucleated were found to display characteristic hexagonal and rhomboidal shapes. In comparing results of particle densities among different ion ratios, there is evidence suggesting that barium to sulfate ratio plays a role of promoter. Wherein, the ratios with higher [Ba2+] concentration were ...


Improving Pain Management In Patients With Sickle Cell Disease Using Machine Learning Techniques, Fan Yang Jan 2020

Improving Pain Management In Patients With Sickle Cell Disease Using Machine Learning Techniques, Fan Yang

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Sickle cell disease (SCD) is an inherited red blood cell disorder that can cause a multitude of complications throughout a patient's life. Pain is the most common complication and a significant cause of morbidity. Since pain is a highly subjective experience, both medical providers and patients express difficulty in determining ideal treatment and management strategies for pain. Therefore, the development of objective pain assessment and pain forecasting methods is critical to pain management in SCD. On the other hand, the rapidly increasing use of mobile health (mHealth) technology and wearable devices gives the ability to build a remote health ...


Finding Data Races In Software Binaries With Symbolic Execution, Nathan D. Jackson Jan 2020

Finding Data Races In Software Binaries With Symbolic Execution, Nathan D. Jackson

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Modern software applications frequently make use of multithreading to utilize hardware resources better and promote application responsiveness. In these applications, threads share the program state, and synchronization mechanisms ensure proper ordering of accesses to the program state. When a developer fails to implement synchronization mechanisms, data races may occur. Finding data races in an automated way is an already challenging problem, but often impractical without source code or understanding how to execute the program under analysis. In this thesis, we propose a solution for finding data races on software binaries and present our prototype implementation BINRELAY. Our solution makes use ...


Enabling Static Program Analysis Using A Graph Database, Jialun Liu Jan 2020

Enabling Static Program Analysis Using A Graph Database, Jialun Liu

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This thesis presents the design, the implementation, and the evaluation of a database-oriented static program analysis engine for the PHP programming language. This engine analyzes PHP programs by representing their semantics using a graph-based data structure, which will be subsequently stored into a graph database. Such scheme will fundamentally facilitate various program analysis tasks such as static taint analysis, visualization, and data mining. Specifically, these complex program analysis tasks can now be translated into built-in declarative graph database operations with rich features. Our engine fundamentally differs from other existing static program analysis systems that mainly leverage intermediate representation (IRs) to ...


Geoaware - A Simulation-Based Framework For Synthetic Trajectory Generation From Mobility Patterns, Jameson D. Morgan Jan 2020

Geoaware - A Simulation-Based Framework For Synthetic Trajectory Generation From Mobility Patterns, Jameson D. Morgan

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Recent advances in location acquisition services have resulted in vast amounts of trajectory data; providing valuable insight into human mobility. The field of trajectory data mining has exploded as a result, with literature detailing algorithms for (pre)processing, map matching, pattern mining, and the like. Unfortunately, obtaining trajectory data for the design and evaluation of such algorithms is problematic due to privacy, ethical, dataset size, researcher access, and sampling frequency concerns. Synthetic trajectories provide a solution to such a problem as they are cheap to produce and are derived from a fully controllable generation procedure. Citing deficiencies in modern synthetic ...


Stream Clustering And Visualization Of Geotagged Text Data For Crisis Management, Nathaniel C. Crossman Jan 2020

Stream Clustering And Visualization Of Geotagged Text Data For Crisis Management, Nathaniel C. Crossman

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In the last decade, the advent of social media and microblogging services have inevitably changed our world. These services produce vast amounts of streaming data, and one of the most important ways of analyzing and discovering interesting trends in the streaming data is through clustering. In clustering streaming data, it is desirable to perform a single pass over incoming data, such that we do not need to process old data again, and the clustering model should evolve over time not to lose any important feature statistics of the data. In this research, we have developed a new clustering system that ...


Design Of A Novel Wearable Ultrasound Vest For Autonomous Monitoring Of The Heart Using Machine Learning, Garrett G. Goodman Jan 2020

Design Of A Novel Wearable Ultrasound Vest For Autonomous Monitoring Of The Heart Using Machine Learning, Garrett G. Goodman

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As the population of older individuals increases worldwide, the number of people with cardiovascular issues and diseases is also increasing. The rate at which individuals in the United States of America and worldwide that succumb to Cardiovascular Disease (CVD) is rising as well. Approximately 2,303 Americans die to some form of CVD per day according to the American Heart Association. Furthermore, the Center for Disease Control and Prevention states that 647,000 Americans die yearly due to some form of CVD, which equates to one person every 37 seconds. Finally, the World Health Organization reports that the number one ...


An Adversarial Framework For Deep 3d Target Template Generation, Walter E. Waldow Jan 2020

An Adversarial Framework For Deep 3d Target Template Generation, Walter E. Waldow

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This paper presents a framework for the generation of 3D models. This is an important problem for many reasons. For example, 3D models are important for systems that are involved in target recognition. These systems use 3D models to train up accuracy on identifying real world object. Traditional means of gathering 3D models have limitations that the generation of 3D models can help overcome. The framework uses a novel generative adversarial network (GAN) that learns latent representations of two dimensional views of a model to bootstrap the network’s ability to learn to generate three dimensional objects. The novel architecture ...