Physical Sciences and Mathematics Commons^™

Few-Shot Malware Detection Using A Novel Adversarial Reprogramming Model, Ekula Praveen Kumar

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The increasing sophistication of malware has made detecting and defending against new strains a major challenge for cybersecurity. One promising approach to this problem is using machine learning techniques that extract representative features and train classification models to detect malware in an early stage. However, training such machine learning-based malware detection models represents a significant challenge that requires a large number of high-quality labeled data samples while it is very costly to obtain them in real-world scenarios. In other words, training machine learning models for malware detection requires the capability to learn from only a few labeled examples. To address …

Vertebrate Assemblages Of The Skelley Limestone (Conemaugh Group : Carboniferous, Gzhelian) In Noble And Muskingum Counties, Ohio, Daniel Austin Cline

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Three outcrops of the Gzhelian-aged Skelley Limestone (Casselman Formation, Conemaugh Group) were explored for vertebrate macrofossils and vertebrate microremains. The purpose of this exploration was to construct a better ecological history of the marine communities in the Late Pennsylvanian of eastern Ohio. Bulk limestone samples were collected, washed with acid, sieved and the resulting residues produced 21 distinct taxa of near-shore marine vertebrates. Osteichthyans were represented by an unknown palaeonisciform, an unknown platysomid, and an unknown palaeoniscoid. Holocephalians were represented by symmoriforms, helodontiforms, cochliodontiforms, and petalodontiforms. Elasmobranch groups included ctenacanthiforms and euselachians which contained representatives of hybodontiforms, protacrodontiforms, and neoselachians. …

Ufuzzer: Lightweight Detection Of Php-Based Unrestricted File Upload Vulnerabilities Via Static-Fuzzing Co-Analysis, Jin Huang, Junjie Zhang, Jialun Liu, Chuang Li

Computer Science and Engineering Faculty Publications

Unrestricted file upload vulnerabilities enable attackers to upload malicious scripts to a web server for later execution. We have built a system, namely UFuzzer, to effectively and automatically detect such vulnerabilities in PHP-based server-side web programs. Different from existing detection methods that use either static program analysis or fuzzing, UFuzzer integrates both (i.e., static-fuzzing co-analysis). Specifically, it leverages static program analysis to generate executable code templates that compactly and effectively summarize the vulnerability-relevant semantics of a server-side web application. UFuzzer then “fuzzes” these templates in a local, native PHP runtime environment for vulnerability detection. Compared to static-analysis-based methods, UFuzzer preserves …

Clustering Of Pain Dynamics In Sickle Cell Disease From Sparse, Uneven Samples, Gary K. Nave Jr, Swati Padhee, Amanuel Alambo, Tanvi Banerjee, Nirmish Shah, Daniel M. Abrams

Computer Science and Engineering Faculty Publications

Irregularly sampled time series data are common in a variety of fields. Many typical methods for drawing insight from data fail in this case. Here we attempt to generalize methods for clustering trajectories to irregularly and sparsely sampled data. We first construct synthetic data sets, then propose and assess four methods of data alignment to allow for application of spectral clustering. We also repeat the same process for real data drawn from medical records of patients with sickle cell disease -- patients whose subjective experiences of pain were tracked for several months via a mobile app. We find that different …

Impact Of Wastes On Some Properties Of Soil Around An Active Dumpsite In Ibadan, Southwestern Nigeria, Oluwatoyin Opeyemi Akintola, Gabriel Oladapo Adeyemi, Oluwayemisi Samuel Olokeogun, Idayat Adewunmi Bodede

Journal of Bioresource Management

Recently most farmers in developing country like Nigeria has resulted to the use of solid wastes as compost to replenish the deteriorated soils while some are farming on the abandoned waste dumpsite due to their richness in organic matter. This study assessed the soil nutrient and fertility status by investigating the influence of wastes (if any) on physical and chemical properties of soils in and around Lapite dumpsite for environmental sustainability. Ten soil samples each collected from three locations: dumpsite, downslope and upslope sites at depth of 0-20cm were analyzed for soil texture, bulk density, porosity, electrical conductivity, pH, organic …

Uncertainty-Aware Visualization In Medical Imaging - A Survey, Christina Gillmann, Dorothee Saur, Thomas Wischgoll, Gerik Scheuermann

Computer Science and Engineering Faculty Publications

Medical imaging (image acquisition, image transformation, and image visualization) is a standard tool for clinicians in order to make diagnoses, plan surgeries, or educate students. Each of these steps is affected by uncertainty, which can highly influence the decision-making process of clinicians. Visualization can help in understanding and communicating these uncertainties. In this manuscript, we aim to summarize the current state-of-the-art in uncertainty-aware visualization in medical imaging. Our report is based on the steps involved in medical imaging as well as its applications. Requirements are formulated to examine the considered approaches. In addition, this manuscript shows which approaches can be …

Nomophobia Before And After The Covid-19 Pandemic-Can Social Media Be Used To Understand Mobile Phone Dependency, Vaishnavi Visweswaraiah, Tanvi Banerjee, William Romine, Sarah Fryman

Computer Science and Engineering Faculty Publications

No abstract provided.

Hydrochemical Assessment Of Groundwater Around Lapite Dumpsite For Irrigation Water Quality In Ibadan, Southwestern Nigeria, Oluwatoyin Opeyemi Akintola, Gabriel Oladapo Adeyemi, Adewunmi Idayat Bodede, Oluwatoyin Oluwatoyin Adekoya, Kekinde O. Babatunde

Journal of Bioresource Management

Due to the increase in population and industrialization growth, most countries in the world depend on groundwater to meet agriculture demands for food production. The increase in water contamination due to indiscriminate solid wastes has necessitated the assessment of water quality and its suitability for agricultural usage. Twenty four groundwater and ten stream water samples were randomly collected from the downslope and upslope side of the dumpsite for all the major physio-chemical parameters. The pH of water samples indicates slightly acidic to alkaline in nature. High concentrations of nitrate, total dissolved solids and electrical conductivity suggest the impact of the …

The Wright State – Lake Campus 2020 – 2021 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 2020 calendar year, spanning across disciplines.

This document contains the Annual Research Report from 2020 and the Research Symposium Program from 2021.

Neuro-Symbolic Deductive Reasoning For Cross-Knowledge Graph Entailment, Monireh Ebrahimi, Md Kamruzzaman Sarker, Federico Bianchi, Ning Xie, Aaron Eberhart, Derek Doran, Hyeongsik Kim, Pascal Hitzler

Computer Science and Engineering Faculty Publications

A significant and recent development in neural-symbolic learning are deep neural networks that can reason over symbolic knowledge graphs (KGs). A particular task of interest is KG entailment, which is to infer the set of all facts that are a logical consequence of current and potential facts of a KG. Initial neural-symbolic systems that can deduce the entailment of a KG have been presented, but they are limited: current systems learn fact relations and entailment patterns specific to a particular KG and hence do not truly generalize, and must be retrained for each KG they are tasked with entailing. We …

Leveraging Natural Language Processing To Mine Issues On Twitter During The Covid-19 Pandemic, Ankita Agarwal, Preetham Salehundam, Swati Padhee, William Romine, Tanvi Wright State University - Main Campus

Computer Science and Engineering Faculty Publications

The recent global outbreak of the coronavirus disease (COVID-19) has spread to all corners of the globe. The international travel ban, panic buying, and the need for self-quarantine are among the many other social challenges brought about in this new era. Twitter platforms have been used in various public health studies to identify public opinion about an event at the local and global scale. To understand the public concerns and responses to the pandemic, a system that can leverage machine learning techniques to filter out irrelevant tweets and identify the important topics of discussion on social media platforms like Twitter …

Topic-Centric Unsupervised Multi-Document Summarization Of Scientific And News Articles, Amanuel Alambo, Cori Lohstroh, Erik Madaus, Swati Padhee, Brandy Foster, Tanvi Banerjee, Krishnaprasad Thirunarayan, Michael Raymer

Computer Science and Engineering Faculty Publications

Recent advances in natural language processing have enabled automation of a wide range of tasks, including machine translation, named entity recognition, and sentiment analysis. Automated summarization of documents, or groups of documents, however, has remained elusive, with many efforts limited to extraction of keywords, key phrases, or key sentences. Accurate abstractive summarization has yet to be achieved due to the inherent difficulty of the problem, and limited availability of training data. In this paper, we propose a topic-centric unsupervised multi-document summarization framework to generate extractive and abstractive summaries for groups of scientific articles across 20 Fields of Study (FoS) in …

Can Subjective Pain Be Inferred From Objective Physiological Data? Evidence From Patients With Sickle Cell Disease, Mark J. Panaggio, Daniel M. Abrams, Fan Yang, Tanvi Banerjee, Nirmish R. Shah

Computer Science and Engineering Faculty Publications

Patients with sickle cell disease (SCD) experience lifelong struggles with both chronic and acute pain, often requiring medical interventMaion. Pain can be managed with medications, but dosages must balance the goal of pain mitigation against the risks of tolerance, addiction and other adverse effects. Setting appropriate dosages requires knowledge of a patient's subjective pain, but collecting pain reports from patients can be difficult for clinicians and disruptive for patients, and is only possible when patients are awake and communicative. Here we investigate methods for estimating SCD patients' pain levels indirectly using vital signs that are routinely collected and documented in …

An Analysis Of C/C++ Datasets For Machine Learning-Assisted Software Vulnerability Detection, Daniel Grahn, Junjie Zhang

Computer Science and Engineering Faculty Publications

As machine learning-assisted vulnerability detection research matures, it is critical to understand the datasets being used by existing papers. In this paper, we explore 7 C/C++ datasets and evaluate their suitability for machine learning-assisted vulnerability detection. We also present a new dataset, named Wild C, containing over 10.3 million individual opensource C/C++ files – a sufficiently large sample to be reasonably considered representative of typical C/C++ code. To facilitate comparison, we tokenize all of the datasets and perform the analysis at this level. We make three primary contributions. First, while all the datasets differ from our Wild C dataset, some …

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 …

Pain Intensity Assessment In Sickle Cell Disease Patients Using Vital Signs During Hospital Visits, Swati Padhee, Amanuel Alambo, Tanvi Banerjee, Arvind Subramaniam, Daniel M. Abrams, Gary K. Nave, Nirmish Shah

Computer Science and Engineering Faculty Publications

Pain in sickle cell disease (SCD) is often associated with increased morbidity, mortality, and high healthcare costs. The standard method for predicting the absence, presence, and intensity of pain has long been self-report. However, medical providers struggle to manage patients based on subjective pain reports correctly and pain medications often lead to further difficulties in patient communication as they may cause sedation and sleepiness. Recent studies have shown that objective physiological measures can predict subjective self-reported pain scores for inpatient visits using machine learning (ML) techniques. In this study, we evaluate the generalizability of ML techniques to data collected from …

A Unified Approach For Constructing Confidence Intervals And Hypothesis Tests Using H-Function, Weizhen Wang

Mathematics and Statistics Faculty Publications

We introduce a general method, named the h-function method, to unify the con- structions of level- exact test and 1− exact confidence interval. Using this method, any confidence interval is improved as follows: i) an approximate interval, including a point estimator, is modified to an exact interval; ii) an exact interval is refined to be an interval that is a subset of the previous one. Two real datasets are used to illustrate the method.

Coloring Permutation-Gain Graphs, Daniel Slilaty

Mathematics and Statistics Faculty Publications

Correspondence colorings of graphs were introduced in 2018by Dvoˇr ́ak and Postle as a generalization of list colorings of graphswhich generalizes ordinary graph coloring. Kim and Ozeki observed thatcorrespondence colorings generalize various notions of signed-graph col-orings which again generalizes ordinary graph colorings. In this notewe state how correspondence colorings generalize Zaslavsky’s notionof gain-graph colorings and then formulate a new coloring theory ofpermutation-gain graphs that sits between gain-graph coloring and cor-respondence colorings. Like Zaslavsky’s gain-graph coloring, our newnotion of coloring permutation-gain graphs has well defined chromaticpolynomials and lifts to colorings of the regular covering graph of apermutation-gain graph

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 …

Analysis Of Amur Honeysuckle Stem Density As A Function Of Spatial Clustering, Horizontal Distance From Streams, Trails, And Elevation In Riparian Forests, Greene County, Ohio, Greg Michael Grierson Jr.

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The non-native invasive shrub Amur honeysuckle, Lonicera maackii (Rupr.) Herder (Gorchov and Trisel, 2003), is one of the most prolific invasive plant species across Midwestern and Northeastern landscapes of the United States. The locations of 2,095 individual Amur honeysuckle stems were geolocated using handheld GPS units in the understory of mixed growth forests at two study sites located approximately 5 km apart in northwestern Greene County, OH. Each site has undergone different levels of anthropogenic disturbance through time. The stem position data was used to measure the spatial clumping distribution and the density of Amur honeysuckle. The spatial clumping of …

Human-Ai Teaming For Dynamic Interpersonal Skill Training, Xavian Alexander Ogletree

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In almost every field, there is a need for strong interpersonal skills. This is especially true in fields such as medicine, psychology, and education. For instance, healthcare providers need to show understanding and compassion for LGBTQ+ and BIPOC (Black, Indigenous, and People of Color), or individuals with unique developmental or mental health needs. Improving interpersonal skills often requires first-person experience with expert evaluation and guidance to achieve proficiency. However, due to limited availability of assessment capabilities, professional standardized patients and instructional experts, students and professionals currently have inadequate opportunities for expert-guided training sessions. Therefore, this research aims to demonstrate leveraging …

The Formation Of Prenucleation Clusters For Calcium Fluoride, Taylor M. Muterspaw

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There have been limited studies on the analysis of the nucleation and precipitation behind calcium fluoride. Earlier studies support a nucleation mechanism in agreement to classical nucleation theory (CNT) in which a surface nucleation mechanism is required for calcium fluoride. This experiment devised using the ISE method to calcium fluoride to find evidence of a nucleation mechanism like that of calcium carbonate (prenucleation cluster pathway). The potential and pH were recorded versus time and the potential data was converted to nCa2+ data of free calcium ions. It was determined that there was evidence of a similar nucleation mechanism for calcium …

Sample Mislabeling Detection And Correction In Bioinformatics Experimental Data, Soon Jye Kho

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Sample mislabeling or incorrect annotation has been a long-standing problem in biomedical research and contributes to irreproducible results and invalid conclusions. These problems are especially prevalent in multi-omics studies in which a large set of biological samples are characterized by multiple types of omics platforms at different times or different labs. While multi-omics studies have demonstrated tremendous value in understanding disease biology and improving patient outcomes, the complexity of these studies may increase opportunities for human error. Fortunately, the interrelated nature of the data collected in multi-omics studies can be exploited to facilitate the identification and, in some cases, correction …

North American Freshwater Snails As Paleoecologic Proxies In Crystal Lake, Medway, Ohio, Jaclyn R. Manker

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This study combines various paleoecological proxies found within a sediment core extracted from Crystal Lake, Medway, Ohio in order to assess the lake’s sensitivity to past climate changes and how that may have affected lake water levels. Crystal Lake is a natural kettle lake formed at the end of the Wisconsin glaciation. It is now surrounded by approximately 500 residential homes and is privately owned by the HOA of Crystal Lake. A sediment core was extracted from Crystal Lake in 2007 and has been carbon dated to 18000 years before present, indicating that it contains a complete sedimentary history from …

Power Scaling Of Ice Floe Sizes In The Weddell Sea, Southern Ocean, Tristan J. Coffey

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The cumulative number versus floe area distribution of seasonal ice floes from four satellite images covering the Summer season (November - February) in the Weddell Sea Antarctica during the summer breakup and melting is fit by two scale-invariant power scaling regimes for the floe areas ranging from 7 to 20 x 108 m2. Scaling exponents, β, for larger floe areas range from -1.5 to -1.7 with an average of -1.6 for floe areas ranging from 6 x 106 to 55 x 107 m2. Scaling exponents, β, for smaller floe areas range from -0.8 to -0.9 with an average of -0.85 …

Effect Of Cloud Cover On Optimum Orientations Of Fixed Solar Panels For Maximum Yearly Energy Collection, Prethew Prasad

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The amount of cloud cover present in the sky is a significant factor when determining the solar radiation impinging on a solar panel. The optimum tilt required to achieve maximum energy impingement on a surface is also influenced by the amount of cloud cover. This work presents a method for determining the optimum tilt angle for a fixed solar panel when a set amount of cloud cover is present in the sky. Fixed tilt angles that have the most incident solar energy over the course of a year as a function of cloud cover, latitude, and azimuthal angle orientation are …

Sediment Nutrient Dynamics In Fondriest Agricultural Settling Pond, Marie Grace Bezold

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Excess loading of nitrogen (N) and phosphorus (P) is a serious global problem and has numerous negative impacts on water quality of aquatic ecosystems including eutrophication, harmful algal blooms, and hypoxia. Anthropogenic activities (such as the Haber-Bosch process, burning of fossil fuels, sewage treatment, and manure reuse) have led to excess N loading to aquatic systems. Sediment N dynamics were examined from Oct 2019 – Oct 2020 in an agricultural settling pond connected to a constructed wetland adjacent to an agricultural field. Intact sediment cores were amended with 15N for continuous-flow incubations to measure denitrification and N fixation rates, as …

Content Adaption And Design In Mobile Learning Of Wind Instruments, Neha Priyadarshani

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People in today's world seek things that are simple to use. Learning is one of the most crucial aspects of the ongoing digital transformation. Everything is now accessible with a single click on mobile devices, making access to instructional materials faster, easier, and more comfortable. It takes time and effort to build abilities and become an expert in the fields of learning, training, and teaching; and music learning demands a great deal of both practice and mentoring. Initially, music teachers and band directors must maintain a steady attention and devote a significant amount of time to manually teaching materials. This …

Goal Management In Multi-Agent Systems, Venkatsampath Raja Gogineni

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Autonomous agents in a multi-agent system coordinate to achieve their goals. However, in a partially observable world, current multi-agent systems are often less effective in achieving their goals. In much part, this limitation is due to an agent's lack of reasoning about other agents and their mental states. Another factor is the agent's inability to share required knowledge with other agents and the lack of explanations in justifying the reasons behind the goal. This research addresses these problems by presenting a general approach for agent goal management in unexpected situations. In this approach, an agent applies three main concepts: goal …

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 …