Physical Sciences and Mathematics Commons^™

The Graphs That Have Antivoltages Using Groups Of Small Order, Vaidy Sivaraman, Dan Slilaty

Mathematics and Statistics Faculty Publications

Given a group Γ of order at most six, we characterize the graphs that have Γ-antivoltages and also determine the list of minor-minimal graphs that have no Γ-antivoltage. Our characterizations yield polynomial-time recognition algorithms for such graphs.

Increasing Expression Of Civic-Engagement Values By Students In A Service-Learning Chemistry Course, Audrey E. Mcgowin, Rebecca Teed

Chemistry Faculty Publications

A service-learning course at a midsized Midwestern research university was modified over a period of six years to integrate best-practice pedagogies that have been shown to increase civic engagement by students. Best-practice pedagogies included regular interaction with community partner(s), significant time spent on the service activity, and regular reflection (written and verbal) on the implications of the service activity. Besides water quality monitoring, students performed private well water analysis, wrote multiple formal reflection papers, and presented a public talk on the results of their project that included significant discussion time with community partners. Authentic expression of civic engagement values was …

Increasing Expression Of Civic-Engagement Values By Students In A Service-Learning Chemistry Course, Audrey Mcgowin, Rebecca Teed

Earth and Environmental Sciences Faculty Publications

A service-learning course at a midsized Midwestern research university was modified over a period of six years to integrate best-practice pedagogies that have been shown to increase civic engagement by students. Best-practice pedagogies included regular interaction with community partner(s), significant time spent on the service activity, and regular reflection (written and verbal) on the implications of the service activity. Besides water quality monitoring, students performed private well water analysis, wrote multiple formal reflection papers, and presented a public talk on the results of their project that included significant discussion time with community partners. Authentic expression of civic engagement values was …

Iamhappy: Towards An Iot Knowledge-Based Cross-Domain Well-Being Recommendation System For Everyday Happiness, Amelia Gyrard, Amit Sheth

Kno.e.sis Publications

Nowadays, healthy lifestyle, fitness, and diet habits have become central applications in our daily life. Positive psychology such as well-being and happiness is the ultimate dream of everyday people’s feelings (even without being aware of it). Wearable devices are being increasingly employed to support well-being and fitness. Those devices produce physiological signals that are analyzed by machines to understand emotions and physical state. The Internetof Things (IoT) technology connects (wearable) devices to the Internet to easily access and process data, even using Web technologies (aka Web of Things).

We design IAMHAPPY, an innovative IoT-based well-being recommendation system to encourage every …

Deep Neural Ranking For Crowdsourced Geopolitical Event Forecasting, Giuseppe Nebbione, Derek Doran, Srikanth Nadella, Brandon Minnery

Computer Science and Engineering Faculty Publications

There are many examples of “wisdom of the crowd” effects in which the large number of participants imparts confidence in the collective judgment of the crowd. But how do we form an aggregated judgment when the size of the crowd is limited? Whose judgments do we include, and whose do we accord the most weight? This paper considers this problem in the context of geopolitical event forecasting, where volunteer analysts are queried to give their expertise, confidence, and predictions about the outcome of an event. We develop a forecast aggregation model that integrates topical information about a question, meta-data about …

Question Answering For Suicide Risk Assessment Using Reddit, Amanuel Alambo, Usha Lokala, Ugur Kursuncu, Krishnaprasad Thirunarayan, Amelia Gyrard, Randon S. Welton, Jyotishman Pathak, Amit P. Sheth

Kno.e.sis Publications

Mental Health America designed ten questionnaires that are used to determine the risk of mental disorders. They are also commonly used by Mental Health Professionals (MHPs) to assess suicidality. Specifically, the Columbia Suicide Severity Rating Scale (C-SSRS), a widely used suicide assessment questionnaire, helps MHPs determine the severity of suicide risk and offer an appropriate treatment. A major challenge in suicide treatment is the social stigma wherein the patient feels reluctance in discussing his/her conditions with an MHP, which leads to inaccurate assessment and treatment of patients. On the other hand, the same patient is comfortable freely discussing his/her mental …

Visual Entailment: A Novel Task For Fine-Grained Image Understanding, Ning Xie, Farley Lai, Derek Doran, Asim Kadav

Computer Science and Engineering Faculty Publications

Existing visual reasoning datasets such as Visual Question Answering (VQA), often suffer from biases conditioned on the question, image or answer distributions. The recently proposed CLEVR dataset addresses these limitations and requires fine-grained reasoning but the dataset is synthetic and consists of similar objects and sentence structures across the dataset. In this paper, we introduce a new inference task, Visual Entailment (VE) - consisting of image-sentence pairs whereby a premise is defined by an image, rather than a natural language sentence as in traditional Textual Entailment tasks. The goal of a trained VE model …

The Magnetocaloric Effect & Performance Of Magnetocaloric Materials In A 1d Active Magnetic Regenerator Simulation, Daniel Nicholas Bayer

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Active magnetic regenerators (AMRs) operate according to the magnetothermal phenomenon known as the magnetocaloric effect (MCE), and are at the forefront of magnetic cooling technology. AMR simulations have been shown to be useful tools in predicting the performance of different magnetocaloric materials (MCMs) without the need to develop a physical prototype. In a search to determine the set of operational parameters which would maximize MCM performance, a 1D simulation of an AMR device has been developed in Matlab. Gadolinium, the most well-documented MCM, is used as a benchmark material to study the effects of varying certain operational parameters such as …

Analyzing Public View Towards Vaccination Using Twitter, Mahajan Rutuja

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Educating people about vaccination tends to target vaccine acceptance and reduction of hesitancy. Social media provides a promising platform for studying public perception regarding vaccination. In this study, we harvested tweets over a year related to vaccines from February 2018 to January 2019. We present a two-stage classifier to: (1) classify the tweets as relevant or non-relevant and (2) categorize them in terms of pro-vaccination, anti-vaccination, or neutral outlook. We found that the classifier was able to distinguish clearly between anti-vaccination and pro-vaccination tweets, but also misclassified many of these as neutral. Using Latent Dirichlet Allocation, we found that two …

The Wright State – Lake Campus 2018 – 2019 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 2018 and the Research Symposium Program from 2019.

10. Corrections To Design And Analysis Of Experiments, Angela Dean, Dan Voss, Danel Draguljic

Design and Analysis of Experiments

Corrections for the provided by the authors for Design and Analysis of Experiments.

Augmenting Flight Imagery From Aerial Refueling, James D. Anderson, Scott Nykl, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

© 2019, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply. When collecting real-world imagery, objects in the scene may be occluded by other objects from the perspective of the camera. However, in some circumstances an occluding object is absent from the scene either for practical reasons or the situation renders it infeasible. Utilizing augmented reality techniques, those images can be altered to examine the affect of the object’s occlusion. This project details a novel method for augmenting real images with virtual objects in a virtual environment. Specifically, images from …

An Interactive Game For Cultural Proficiencytraining Featuring Virtual Reality Immersion, Paul J. Hershberger, Blaine A. Klingler, Matt Davis, Sankalp Mishra, Miteshkumar Vasoya, Dixit Patel, Aishwarya Bositty, Tanuja Addanki, Frank A. Allen, Suneesh Menon, Sabrina Neeley, Angie Castle, Todd Pavlak, Yong Pei, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

No abstract provided.

Visual Entailment Task For Visually-Grounded Language Learning, Ning Xie, Farley Lai, Derek Doran, Asim Kadav

Computer Science and Engineering Faculty Publications

We introduce a new inference task - Visual Entailment (VE) - which differs from traditional Textual Entailment (TE) tasks whereby a premise is defined by an image, rather than a natural language sentence as in TE tasks. A novel dataset SNLI-VE (publicly available at https://github.com/necla-ml/SNLI-VE) is proposed for VE tasks based on the Stanford Natural Language Inference corpus and Flickr30k. We introduce a differentiable architecture called the Explainable Visual Entailment model (EVE) to tackle the VE problem. EVE and several other state-of-the-art visual question answering (VQA) based models are evaluated on the SNLI-VE dataset, facilitating grounded language understanding and providing …

Xr-Based Workforce Develop In The Southwestern Region Of Ohio, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

No abstract provided.

Use Of Virtual Reality Technology In Medical Training And Patient Rehabilitation, Sankalp Mishra

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Coaching patients to follow the rehabilitation routines correctly and timely after surgery is often a challenge due to the limited medical knowledge of patients and limited availability of clinicians. Similarly, it is also a challenge to train medical professionals with both the technical and communication skills required in their practices. The recent emergence of VR technologies shines the light on improving the current training practices. In this thesis research, I will look at the development and application of VR-based immersive training games for two particular cases: 1. Post hand surgery rehab; and, 2. Training for Social determinants of health (SDOH) …

Accelerating Reverse Engineering Image Processing Using Fpga, Matthew Joshua Harris

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In recent decades, field programmable gate arrays (FPGAs) have evolved beyond simple, expensive computational components with minimal computing power to complex, inexpensive computational engines. Today, FPGAs can perform algorithmically complex problems with improved performance compared to sequential CPUs by taking advantage of parallelization. This concept can be readily applied to the computationally dense field of image manipulation and analysis. Processed on a standard CPU, image manipulation suffers with large image sets processed by highly sequential algorithms, but by carefully adhering to data dependencies, parallelized FPGA functions or kernels offer the possibility of significant improvement through threaded CPU functions. This thesis …

Mapping Of Suspected Unmarked Burials As High Resistivity Anomalies At The Stevenson Cemetery Near Xenia, Ohio, Philip Alexander Marsh

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The purpose of this thesis was to further study geophysical anomalies discovered and mapped by Shank (2013) at the Stevenson Cemetery, Greene County, Ohio, with the goal of delineating any resistivity anomaly possibly associated with suspected, but unmarked, burial sites. The previous study delineated geophysical anomalies using electromagnetic (EM), magnetic, and ground penetrating radar surveys, which were interpreted to represent unmarked burial sites. A hand-drawn map from the 1950’s shows a pattern of gravesites across this area, and three aligned subtle depressions are present at the surface in the study area. The focus of this study was to expand the …

Empathi: An Ontology For Emergency Managing And Planning About Hazard Crisis, Manas Gaur, Kaeedeh Shekarpour, Amelia Gyrard, Amit P. Sheth

Kno.e.sis Publications

In the domain of emergency management during hazard crises, having sufficient situational awareness information is critical. It requires capturing and integrating information from sources such as satellite images, local sensors and social media content generated by local people.
A bold obstacle to capturing, representing and integrating such heterogeneous and diverse information is lack of a proper ontology which properly conceptualizes this domain, aggregates and unifies datasets. Thus, in this paper, we introduce empathi ontology which conceptualizes the core concepts describing the domain of emergency managing and planning of hazard crises.
Although empathi has a coarse-grained view, it considers the necessary …

Adaptive Knowledge Networks: A Time Capsule, Swati Padhee, Anurag Illendula, Amit Sheth, Krishnaprasad Thirunarayan, Valerie L. Shalin

Kno.e.sis Publications

❖ Real world events are dynamic in nature Periodic events e.g. US Presidential Election Non-periodic events e.g. Cyclone Idai

❖ Need for real-time predictive analysis, trend analysis, spatio-temporal decision making, public opinion analysis for events.

❖ Current state-of-the-art curates dynamic knowledge graph from structured text.

❖ We propose creating an Adaptive Knowledge Network from incoming real-time multimodal spatio-temporally evolving data.

Automatic Identification Of Individual Drugs In Death Certificates, Soon Jye Kho, Amit Sheth, Olivier Bodenreider

Kno.e.sis Publications

Background:

Establishing trends of drug overdoses requires the identification of individual drugs in death certificates, not supported by coding with the International Classification of Diseases. However, identifying drug mentions from the literal portion of death certificates remains challenging due to the variability of drug names.

Objectives:

To automatically identify individual drugs in death certificates.

Methods:

We use RxNorm to collect variants for drug names (generic names, synonyms, brand names) and we algorithmically generate common misspellings. We use this automatically compiled list to identify drug mentions from 703,106 death certificates and compare the performance of our automated approach to that of …

Static Evaluation Of Type Inference And Propagation On Global Variables With Varying Context, Ivan Frasure

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Software reverse engineering (SRE) is a broad field with motivations ranging from verifying or documenting gordian source code files to understanding and reimplementing binary object files and executables. SRE of binaries is exceptionally compelling and challenging due to large amounts of information that can be lost in the compilation progress. A central area in SRE is type inference. Type inference is built around a fundamental step in understanding the behavior of a binary, recovering the types of data in the program. Type inference has many unique techniques in both static and dynamic type inference systems that have been implemented in …

Ammonium Cycling And Nitrifier Community Composition In Eutrophic Waters Affected By Cyanobacterial Harmful Algal Blooms, Justyna J. Hampel

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Non-point source nitrogen (N) from agriculture is a main driver of eutrophication in aquatic systems, which often manifests as toxin producing cyanobacterial harmful algal blooms (cyanoHABs). Non-N2 fixing cyanobacteria, such as Microcystis, thrive on chemically reduced N forms (e.g., ammonium (NH4+) and urea) used as the main N form in fertilizer. NH4+ turnover rates are important components of the aquatic N cycle in eutrophic lakes affected by cyanoHABs. Regeneration of NH4+ can contribute to the internal cycling of NH4+, which can sustain cyanoHABs when external loads are low. Additionally, NH4+ uptake by cyanobacteria competes directly with nitrification, another important pathway …

Paradoxical Behavior In Groundwater Levels In Response To Precipitation Events, Alexandra Shelters

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Groundwater levels are expected to fluctuate with precipitation, rising when precipitation increases and falling when it decreases. However, observations often show that groundwater levels rise in months when precipitation has decreased from the previous month, or alternately, falls in months when precipitation has increased from the previous month. Such paradoxical behavior is documented in a 30-year record for a monitoring well in southwestern Ohio. This record was analyzed to evaluate the hypothesis that mass balance controls the change in groundwater level such that changes cannot be predicted solely from monthly changes in precipitation. Though precipitation may vary from one month …

Securing Modern Cyberspace Using A Multi-Faceted Approach, Yu Li

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Security has become one of the most significant concerns for our cyberspace. Securing the cyberspace, however, becomes increasingly challenging. This can be attributed to the rapidly growing diversities and complexity of the modern cyberspace. Specifically, it is not any more dominated by connected personal computers (PCs); instead, it is greatly characterized by cyber-physical systems (CPS), embedded systems, dynamic services, and human-computer interactions. Securing modern cyberspace therefore calls for a multi-faceted approach capable of systematically integrating these emerging characteristics. This dissertation presents our novel and significant solutions towards this direction. Specifically, we have devised automated, systematic security solutions to three critical …

Recognition Of Incomplete Objects Based On Synthesis Of Views Using A Geometric Based Local-Global Graphs, Michael Christopher Robbeloth

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The recognition of single objects is an old research field with many techniques and robust results. The probabilistic recognition of incomplete objects, however, remains an active field with challenging issues associated to shadows, illumination and other visual characteristics. With object incompleteness, we mean missing parts of a known object and not low-resolution images of that object. The employment of various single machine-learning methodologies for accurate classification of the incomplete objects did not provide a robust answer to the challenging problem. In this dissertation, we present a suite of high-level, model-based computer vision techniques encompassing both geometric and machine learning approaches …

Preference, Performance, And Selection Of Historic And Novel Hosts By Emerald Ash Borer, Agrilus Planipennis Fairmaire (Coleoptera: Buprestidae), Donnie L. Peterson

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North American and European ash trees are highly susceptible to emerald ash borer (EAB, Agrilus planipennis). This buprestid kills hosts via larva feeding on vascular tissue which eventually kills the host plant. Two new hosts have recently been found to support larval development of EAB. White fringetrees (Chionathus virginicus) were found attacked by EAB in 2014 and since then have been found to be attacked throughout other parts of the United States, while olive (Olea europaea) has only experimentally been found to support larvae to adulthood. Chemical profiles of these two plants were collected and analyzed to determine how their …

Islands Of Fitness Compact Genetic Algorithm For Rapid In-Flight Control Learning In A Flapping-Wing Micro Air Vehicle: A Search Space Reduction Approach, Kayleigh E. Duncan

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On-going effective control of insect-scale Flapping-Wing Micro Air Vehicles could be significantly advantaged by active in-flight control adaptation. Previous work demonstrated that in simulated vehicles with wing membrane damage, in-flight recovery of effective vehicle attitude and vehicle position control precision via use of an in-flight adaptive learning oscillator was possible. Most recent approaches to this problem employ an island-of-fitness compact genetic algorithm (ICGA) for oscillator learning. The work presented provides the details of a domain specific search space reduction approach implemented with existing ICGA and its effect on the in-flight learning time. Further, it will be demonstrated that the proposed …

Knowledge-Enabled Entity Extraction, Hussein S. Al-Olimat

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Information Extraction (IE) techniques are developed to extract entities, relationships, and other detailed information from unstructured text. The majority of the methods in the literature focus on designing supervised machine learning techniques, which are not very practical due to the high cost of obtaining annotations and the difficulty in creating high quality (in terms of reliability and coverage) gold standard. Therefore, semi-supervised and distantly-supervised techniques are getting more traction lately to overcome some of the challenges, such as bootstrapping the learning quickly. This dissertation focuses on information extraction, and in particular entities, i.e., Named Entity Recognition (NER), from multiple domains, …

Knowledge Graph Reasoning Over Unseen Rdf Data, Bhargavacharan Reddy Kaithi

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In recent years, the research in deep learning and knowledge engineering has made a wide impact on the data and knowledge representations. The research in knowledge engineering has frequently focused on modeling the high level human cognitive abilities, such as reasoning, making inferences, and validation. Semantic Web Technologies and Deep Learning have an interest in creating intelligent artifacts. Deep learning is a set of machine learning algorithms that attempt to model data representations through many layers of non-linear transformations. Deep learning is in- creasingly employed to analyze various knowledge representations mentioned in Semantic Web and provides better results for Semantic …