Physical Sciences and Mathematics Commons^™

Development Of A Computer Model To Simulate Battery Performance For Use In Renewable Energy Simulations, Arjun Sundararajan

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Renewable and clean energy has been the driving force behind the booming storage industry. The need for producing energy from clean and quickly replenishable energy sources has never been as high as it is now. However, renewable energy only supplies a little over a quarter of the world’s electricity needs and much less of the world’s total energy requirements. One reason is the intermittent nature of renewable energy. Inexpensive and convenient storage technologies are required to solve this issue. It is believed that batteries offer the most viable solution to conquer the problem of renewable energy intermittency. To aid the …

Utilizing Rotational Energy In Wind Turbine Blades With The Flywheel Mechanism And Predicting The Power Output By Neural Networking, Anamika Mishra

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As we expand and innovate for better and safer living, there will always be a need for new energy sources. By replacing fossil fuels, renewable energy is becoming a viable option for primary power generation. That is why researchers are turning their attention to renewable energy sources and ways of making the most of them. WIND ENERGY is a promising renewable and clean energy source harvested from the wind which is plentiful on the planet. We already have the technology to harvest it, but the efficiency and power output are not optimal. In this thesis, to enhance the energy harvesting …

Applying Cognitive Measures In Counterfactual Prediction, Lori A. Mahoney

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Counterfactual reasoning can be used in task-switching scenarios, such as design and planning tasks, to learn from past behavior, predict future performance, and customize interventions leading to enhanced performance. Previous research has focused on external factors and personality traits; there is a lack of research exploring how the decision-making process relates to both task-switching and counterfactual predictions. The purpose of this dissertation is to describe and explain individual differences in task-switching strategy and cognitive processes using machine learning techniques and linear ballistic accumulator (LBA) models, respectively, and apply those results in counterfactual models to predict behavior. Applying machine learning techniques …

Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger

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The additive manufacturing (AM) field is striving to identify anomalies in laser powder bed fusion (LPBF) using multi-sensor in-process monitoring paired with machine learning (ML). In-process monitoring can reveal the presence of anomalies but creating a ML classifier requires labeled data. The present work approaches this problem by printing hundreds of Inconel-718 coupons with different processing parameters to capture a wide range of process monitoring imagery with multiple sensor types. Afterwards, the process monitoring images are encoded into feature vectors and clustered to isolate groups in each sensor modality. Four texture representations were learned by training two convolutional neural network …

Utilizing Rotational Energy In Wind Turbine Blades With The Flywheel Mechanism And Predicting The Power Output By Neural Networking, Anamika Mishra

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As we expand and innovate for better and safer living, there will always be a need for new energy sources. By replacing fossil fuels, renewable energy is becoming a viable option for primary power generation. That is why researchers are turning their attention to renewable energy sources and ways of making the most of them. WIND ENERGY is a promising renewable and clean energy source harvested from the wind which is plentiful on the planet. We already have the technology to harvest it, but the efficiency and power output are not optimal. In this thesis, to enhance the energy harvesting …

Evaluating The Performance Of Using Speaker Diarization For Speech Separation Of In-Person Role-Play Dialogues, Raveendra Medaramitta

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Development of professional communication skills, such as motivational interviewing, often requires experiential learning through expert instructor-guided role-plays between the trainee and a standard patient/actor. Due to the growing demand for such skills in practices, e.g., for health care providers in the management of mental health challenges, chronic conditions, substance misuse disorders, etc., there is an urgent need to improve the efficacy and scalability of such role-play based experiential learning, which are often bottlenecked by the time-consuming performance assessment process. WSU is developing ReadMI (Real-time Assessment of Dialogue in Motivational Interviewing) to address this challenge, a mobile AI solution aiming to …

The Family Of Bicircular Matroids Closed Under Duality, Vaidy Sivaraman, Daniel Slilaty

Mathematics and Statistics Faculty Publications

We characterize the 3-connected members of the intersection of the class of bicircular and cobi- circular matroids. Aside from some exceptional matroids with rank and corank at most 5, this class consists of just the free swirls and their minors.

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

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

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.

Covid-19 And Mental Health/Substance Use Disorders On Reddit: A Longitudinal Study, Amanuel Alambo, Swati Padhee, Tanvi Banerjee, Krishnaprasad Thirunarayan

Computer Science and Engineering Faculty Publications

COVID-19 pandemic has adversely and disproportionately impacted people suffering from mental health issues and substance use problems. This has been exacerbated by social isolation during the pandemic and the social stigma associated with mental health and substance use disorders, making people reluctant to share their struggles and seek help. Due to the anonymity and privacy they provide, social media emerged as a convenient medium for people to share their experiences about their day to day struggles. Reddit is a well-recognized social media platform that provides focused and structured forums called subreddits, that users subscribe to and discuss their experiences with …

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

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

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 …

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 (7.4-10.4 %) and …

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 abundance …

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 …

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, conductivity, …

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 …

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

Lake Campus Research Symposium Reports

This report provides a listing of the scholarly endeavors from Lake Campus during the 2019 calendar year, spanning across disciplines.

This document contains the Annual Research Report from 2019 and the Research Symposium Program from 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 cycle in F, there …

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 intervention …

Anthrax Event Detection: Analysis Of Public Opinion Using Twitter During Anthrax Scares, The Mueller Investigation, And North Korean Threats, Michele E. Miller

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When people allow fear to drive their decision making, they often make decisions that do more harm than good. Examples of this include stocking up on ciprofloxacin, flooding doctors’ offices and buying black market antibiotics after the anthrax attacks of 2001. Therefore, it is important to be able to address what people are saying when another anthrax attack occurs. Supervised and unsupervised machine learning methodologies can be utilized to detect an event, classify the tweets by event, and to determine the main topics of discussion. Over the period of data collection, twenty events were detected. Three of these events concerned …

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.

Predicting Early Indicators Of Cognitive Decline From Verbal Utterances, Swati Padhee, Anurag Illendula, Megan Sadler, Valerie L. Shalin, Tanvi Banerjee, Krishnaprasad Thirunarayan, William Romine

Computer Science and Engineering Faculty Publications

Dementia is a group of irreversible, chronic, and progressive neurodegenerative disorders resulting in impaired memory, communication, and thought processes. In recent years, clinical research advances in brain aging have focused on the earliest clinically detectable stage of incipient dementia, commonly known as mild cognitive impairment (MCI). Currently, these disorders are diagnosed using a manual analysis of neuropsychological examinations. We measure the feasibility of using the linguistic characteristics of verbal utterances elicited during neuropsychological exams of elderly subjects to distinguish between elderly control groups, people with MCI, people diagnosed with possible Alzheimer's disease (AD), and probable AD. We investigated the performance …

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

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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.

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 …

Development Of Embedded Atom Method Interatomic Potentials For Ge-Sn-Si Ternary And Constituent Binary Alloys For Modeling Material Crystallization, Sudip Acharya

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Group IV elements based nanoelectronics devices (mainly Si and Ge based devices) have been developed and improved over a long period of time and are the most influencing materials of semiconductor electronics, but due to their indirect bandgap their use in optoelectronics is limited. Alternatively, new Group IV alloys comprised of Ge, Si, and Sn semiconductor materials have emerged as attractive options for various electronic and optoelectronic applications. The binary and ternary alloys provide strain and energy bandgap engineering by controlling element content, a route for realizing direct-transition semiconductors, improvement in interface and defect properties, and a reduction of the …

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.