Physical Sciences and Mathematics Commons^™

Quantum Chemical Pka Estimation Of Carbon Acids, Saturated Alcohols, And Ketones Via Quantitative Structure-Activity Relationships, Corey Adam Baldasare

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Acid dissociation constants, often expressed as pKa values, afford vital information with regards to molecular behavior in various environments and are of significance in fields of organic, inorganic, and medicinal chemistry. Several quantitative structure-activity relationships (QSARs) were developed that correlate experimental pKas for a given class of compounds with a descriptor(s) calculated using density functional theory at the B3LYP/6-31+G** level utilizing the CPCM solvent model. A set of carbon acids provided a good final QSAR model of experimental aqueous pKas versus ΔEH2O (R2 = 0.9647) upon removal of three aldehydes as outliers. A study of saturated alcohols offered a final …

The Fate Of Anthropogenic Nitrogen Along Hydrologic Continuums: Patterns Of Transformation And Recycling In A Eutrophic Lake And Coastal Marine Sediments, Daniel K. Hoffman

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Eutrophication of aquatic systems can have cascading effects along hydrological continua from watersheds to coasts that result in impaired ecosystem health. In freshwater systems, blooms of toxic, non-nitrogen (N) fixing cyanobacteria (cyanoHABs), such as Microcystis, proliferate due to external loading of chemically reduced forms of N (e.g., ammonium (NH4+) and urea), which promote growth and toxin production. In coastal marine systems, nutrient loading can promote harmful algae blooms and threaten vulnerable, native vegetation, such as seagrasses, which provide valuable ecosystem services but are under threat globally from anthropogenic stressors. This dissertation focuses on NH4+ cycling in the water column of …

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 trajectory …

Marine Vertebrate Communities From The Cisuralian Epoch (Permian Period) Of Central North America, Ryan C. Shell

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Marine vertebrates from the Cisuralian Epoch early Permian Period) are rare in the global fossil record. In particular, species-rich faunas from individual localities are poorly represented, with single occurrence localities that do not fully capture faunal tends in marine vertebrate ecology across this interval. This dissertation helps to close this gap by reporting marine vertebrate fossils from five localities across central North America, containing four to 15 unequivocal vertebrate taxa, as well as a new single occurrence locality near the Carboniferous-Permian boundary. This survey includes representatives from the first three of the four Cisuralian faunal stages, and is the result …

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 …

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 …

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.

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 …

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.

Automated Vehicle Electronic Control Unit (Ecu) Sensor Location Using Feature-Vector Based Comparisons, Gregory S. Buthker

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In the growing world of cybersecurity, being able to map and analyze how software and hardware interact is key to understanding and protecting critical embedded systems like the Engine Control Unit (ECU). The aim of our research is to use our understanding of the ECU's control flow attained through manual analysis to automatically map and identify sensor functions found within the ECU. We seek to do this by generating unique sets of feature vectors for every function within the binary file of a car ECU, and then using those feature sets to locate functions within each binary similar to their …

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.

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 …

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.

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, …

Lead In Tap Water Of Public Schools Near Dayton, Ohio, Baylee Stark

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Lead (Pb) is a human-health concern, especially with regard to exposures of children. Lead contaminated drinking water is a primary route of exposure for children; however, water sampling for Pb is voluntary in schools with a public water supply. This study examined Pb in tap water from public schools around Dayton, OH. Schools were selected to span a range of ages (construction year) and community socioeconomic status. Of the 28 schools contacted, seven responded "affirmatively" to sampling, two responded "negatively", and 19 did not respond. None of the schools that were sampled had Pb concentrations exceeding the U.S. EPA guidelines …

Transmission Electron Microscopy Analysis Of Silicon-Doped Beta-Gallium Oxide Films Grown By Pulsed Laser Deposition, Cynthia Thomason Bowers

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Due to the large band gap of β-Ga2O3 and recent improvements toward high quality native substrates and the ability to shallow dope epitaxial β-Ga2O3 it is an attractive material for applications in power electronic devices. Such devices require advances in the areas of thin film growth and carrier concentration control to deliver high mobility films appropriate for the device structures. Transmission electron microscopy (TEM) analysis can provide information concerning doping, crystal structure, and internal strain which will be valuable to assess the role of defects and impurities on the transport properties for feedback to optimize the bulk and epitaxial growth …

Kbot: Knowledge-Enabled Personalized Chatbot For Self-Management Of Asthma In Pediatric Population, Dipesh Kadariya

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Asthma, chronic pulmonary disease, is one of the major health issues in the United States. Given its chronic nature, the demand for continuous monitoring of patient’s adherence to the medication care plan, assessment of their environment triggers, and management of asthma control level can be challenging in traditional clinical settings and taxing on clinical professionals. A shift from a reactive to a proactive asthma care can improve health outcomes and reduce expenses. On the technology spectrum, smart conversational systems and Internet-of-Things (IoTs) are rapidly gaining popularity in the healthcare industry. By leveraging such technological prevalence, it is feasible to design …

Detecting Malicious Behavior In Openwrt With Qemu Tracing, Jeremy Porter

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In recent years embedded devices have become more ubiquitous than ever before and are expected to continue this trend. Embedded devices typically have a singular or more focused purpose, a smaller footprint, and often interact with the physical world. Some examples include routers, wearable heart rate monitors, and thermometers. These devices are excellent at providing real time data or completing a specific task quickly, but they lack many features that make security issues more obvious. Generally, Embedded devices are not easily secured. Malware or rootkits in the firmware of an embedded system are difficult to detect because embedded devices do …

Llvm-Ir Based Decompilation, Ilsoo Jeon

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Decompilation is a process of transforming an executable program into a source-like high-level language code, which plays an important role in malware analysis, and vulnerability detection. In this thesis, we design and implement the middle end of a decompiler framework, focusing on Low Level Language properties reduction using the optimization techniques, propagation and elimination. An open-source software tool, dagger, is used to translate binary code to LLVM (Low Level Virtual Machine) Intermediate Representation code. We perform data flow analysis and control flow analysis on the LLVM format code to generate high-level code using a Functional Programming Langauge (FPL), Haskell. The …

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 …

Software Implementations And Applications Of Elliptic Curve Cryptography, Kirill Kultinov

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Elliptic Curve Cryptography (ECC) is a public-key cryptography system. Elliptic Curve Cryptography (ECC) can achieve the same level of security as the public-key cryptography system, RSA, with a much smaller key size. It is a promising public key cryptography system with regard to time efficiency and resource utilization. This thesis focuses on the software implementations of ECC over finite field GF(p) with two distinct implementations of the Big Integer classes using character arrays, and bit sets in C++ programming language. Our implementation works on the ECC curves of the form y^2 = x^3 + ax + b (mod p). The …