Physical Sciences and Mathematics Commons^™

Preliminary Investigation Of Walking Motion Using A Combination Of Image And Signal Processing, Bradley Schneider, Tanvi Banerjee

Kno.e.sis Publications

We present the results of analyzing gait motion in first-person video taken from a commercially available wearable camera embedded in a pair of glasses. The video is analyzed with three different computer vision methods to extract motion vectors from different gait sequences from four individuals for comparison against a manually annotated ground truth dataset. Using a combination of signal processing and computer vision techniques, gait features are extracted to identify the walking pace of the individual wearing the camera as well as validated using the ground truth dataset. Our preliminary results indicate that the extraction of activity from the video …

Analyzing Clinical Depressive Symptoms In Twitter, Amir Hossein Yazdavar, Hussein S. Al-Olimat, Tanvi Banerjee, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

350 million people are suffering from clinical depression worldwide.

What Motivates High School Students To Take Precautions Against The Spread Of Influenza? A Data Science Approach To Latent Modeling Of Compliance With Preventative Practice, William L. Romine, Tanvi Banerjee, William R. Folk, Lloyd H. Barrow

Kno.e.sis Publications

– This study focuses on a central question: What key behavioral factors influence high school students’ compliance with preventative measures against the transmission of influenza? We use multilevel logistic regression to equate logit measures for eight precautions to students’ latent compliance levels on a common scale. Using linear regression, we explore the efficacy of knowledge of influenza, affective perceptions about influenza and its prevention, prior illness, and gender in predicting compliance. Hand washing and respiratory etiquette are the easiest precautions for students, and hand sanitizer use and keeping the hands away from the face are the most difficult. Perceptions of …

Semantic, Cognitive, And Perceptual Computing: Paradigms That Shape Human Experience, Amit P. Sheth, Pramod Anantharam, Cory Henson

Kno.e.sis Publications

Unlike machine-centric computing, in which efficient data processing takes precedence over contextual tailoring, human-centric computation provides a personalized data interpretation that most users find highly relevant to their needs. The authors show how semantic, cognitive, and perceptual computing paradigms work together to produce actionable information.

A Performance Analysis Framework For Coreference Resolution Algorithms, Chandankumar Johakhim Patel

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This thesis entitled A Performance Analysis Framework for Coreference Resolution Algorithms, focuses on the topic of coreference resolution of semantic datasets. In order for Big Data analytics to be effective, it is essential to develop automated algorithms capable of integrating multiple datasets that contain data about a particular person or other entity. Accomplishing this necessitates coreference resolution; for example, determining that J. Doe in one dataset refers to the same person as Jonathan Doe Jr. in another dataset. There are many existing coreference resolution algorithms, but there are only a few basic design decisions to be made by such systems …

Openthinning: Fast 3d Thinning Based On Local Neighborhood Lookups, Tobias Post, Christina Gillmann, Thomas Wischgoll, Hans Hagen

Computer Science and Engineering Faculty Publications

3D Thinning is an often required image processing task in order to perform shape analysis in various applications. For researchers in these domains, a fast, flexible and easy to access implementation is required. Open source solutions, as the Insights Segmentation and Registration Toolkit (ITK), are often used for image processing and visualization tasks, due to their wide range of provided algorithms. Unfortunately, ITK’s thinning implementation is computational expensive and allows solely one specific thinning approach. Therefore, this work presents OpenThinning, an open source thinning solution for 3D image data. The implemented algorithm evaluates a moving local neighborhood to find deletable …

Cardiovascular Dieseases: From Data Generation To Analysis, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Cardiovascular diseases remain the leading cause of death in Western societies. This presentation will provide insight into the use of expert knowledge and models to derive diagnostic tools that have the potential to aid in the diagnosis of diffuse cardiovascular diseases that tend to be more difficult to detect in CT angiograms. In order to develop these methods more basic research is needed to prove the validity of the approach, including validation of accuracy as well as approach itself. For that, specimens of porcine hearts were prepared and then analyzed followed by a statistical comparison between computed and optical measurements. …

Super-Resolution Reconstruction Of Mri, Sara Gharabaghi, Thomas Wischgoll, Nasser H. Kashou

Computer Science and Engineering Faculty Publications

Magnetic Resonance Imaging (MRI) is a non-invasive technique that is used in clinical applications such as diseases diagnosis and monitoring and treatment progress. Although, MRI scans typically have high in-plane resolution but they have very poor resolution in slice direction. Furthermore, in some applications with limited acquisition time or where the subject is moving, increased slice thickness or inter-slice space (slice gaps) may be used which results in poor resolution MRI.

In this research, we propose a novel Super Resolution (SR) technique for reconstructing High-Resolution (HR) MRI using a sequence of orthogonal Low-Resolution (LR) MRI scans.

The resolution of this …

Hpc Enabled Data Analytics For High-Throughput High-Content Cellular Analysis, Ross A. Smith, Rhonda J. Vickery, Jack Harris, Sara Gharabaghi, Thomas Wischgoll, David Short, Robert Trevino, Steven A. Kawamoto, Thomas J. Lamkin, Kevin Schoen, Eric E. Bardes, Scott C. Tabar, Bruce J. Aronow

Computer Science and Engineering Faculty Publications

Biologists doing high-throughput high-content cellular analysis are generally not computer scientists or high performance computing (HPC) experts, and they want their workflow to support their science without having to be. We describe a new HPC enabled data analytics workflow with a web interface, HPC pipeline for analysis, and both traditional and new analytics tools to help them transition from a single workstation mode of operation to power HPC users. This allows the processing of multiple plates over a short period of time to ensure timely query and analysis to match potential countermeasures to individual responses.

A Semi-Automated Computer Program For Assessment Of Skeletal Maturity In Children, Sara Gharabaghi, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

In pediatric patients, skeletal maturity is an important tool for detection of hormonal, growth or genetic disorders. The Fels method is a well-known visual assessment method in which the skeletal age is estimated by grading 98 skeletal indicators in the hand-wrist radiographic (x-ray) image. These indicators are features that reflect the three-dimensional shape of the bones and change during the maturation process. Generally, the Fels indicators could be categorized into three main groups of the status of ossification, the ratios of bone widths, and epiphysealdiaphyseal fusion.

Building The Web Of Knowledge With Smart Iot Applications, Amelie Gyrard, Pankesh Patel, Amit P. Sheth, Martin Serrano

Kno.e.sis Publications

The Internet of Things (IoT) is experiencing fast adoption because of its positive impact to change all aspects of our lives, from agriculture in rural areas, to health and wellness, to smart home and smart-x applications in cities. The development of IoT applications and deployment of smart IoT-based solutions is just starting; smart IoT applications will modify our physical world and our interaction with cyber spaces, from how we remotely control appliances at home to how we care for patients or elderly persons. The massive deployment of IoT devices represents a tremendous economic impact and at the same time offers …

A Study Of Social Web Data On Buprenorphine Abuse Using Semantic Web Technology, Raminta Daniulaityte, Amit P. Sheth

Kno.e.sis Publications

The Specific Aims of this application are to use a paradigmatic approach that combines Semantic Web technology, Natural Language Processing and Machine Learning techniques to:

1) Describe drug users’ knowledge, attitudes, and behaviors related to the non-medical use of Suboxone and Subutex as discussed on Web-based forums.
2) Identify and describe temporal patterns of non-medical use of Suboxone and Subutex as discussed on Web-based forums.

The research was carried out by an interdisciplinary team of members of the Center for Interventions, Treatment and Addictions Research (CITAR) and the Ohio Center of Excellence in Knowledge- enabled Computing (Kno.e.sis) at Wright State …

Co-Evolution Of Rdf Datasets, Sidra Faisal, Kemele M. Endris, Saeedeh Shekarpour, Sören Auer, Maria-Esther Vidal

Kno.e.sis Publications

Linking Data initiatives have fostered the publication of large number of RDF datasets in the Linked Open Data (LOD) cloud, as well as the development of query processing infrastructures to access these data in a federated fashion. However, different experimental studies have shown that availability of LOD datasets cannot be always ensured, being RDF data replication required for envisioning reliable federated query frameworks. Albeit enhancing data availability, RDF data replication requires synchronization and conflict resolution when replicas and source datasets are allowed to change data over time, i.e., co-evolution management needs to be provided to ensure consistency. In this paper, …

Uncertainty-Awareness In Open Source Visualization Solutions, Christina Gillmann, Thomas Wischgoll, Hans Hagen

Computer Science and Engineering Faculty Publications

The popularity of open source tools is constantly increasing, as they offer the possibility to quickly create and use visualizations of arbitrary data sources. As the positive effects of uncertainty communication to all kinds of visualizations were discussed over the past years in the academic world, this work examines the uncertaintyawareness of open source solutions. Through a categorization and classification of available tools, this paper identifies the problems in uncertainty-awareness of available open source solutions. To solve this problem, a new paradigm of data handling that extends raw datasets by its uncertainty is suggested

Resqu: A Framework For Automatic Evaluation Of Knowledge-Driven Automatic Summarization, Nishita Jaykumar

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Automatic generation of summaries that capture the salient aspects of a search resultset (i.e., automatic summarization) has become an important task in biomedical research. Automatic summarization offers an avenue for overcoming the information overload problem prevalent in large online digital libraries. However, across many of the knowledge-driven approaches for automatic summarization it is not always clear which features highly impact or influence the quality of a summary. Instead, there has been considerable focus on utilizing schema knowledge to facilitate browsing and exploration of generated summaries a posteriori. Informative features should not be ignored, since they could be utilized to help …

Computer Graphics And Visualization Based Analysis And Record System For Hand Surgery And Therapy Practice, Venkatamanikanta Subrahmanyakartheek Gokavarapu

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In this thesis, we have designed and developed a computer graphics and visualization based analysis and record system for hand surgery and therapy practice. In particular, we have designed and developed three novel technologies: (i) model-based data compression for hand motion records (ii) model-based surface area estimation of a human hand and (iii) an emulated study of hand wound area estimation. First, we have presented a new data compression technique to better address the needs of electronic health record systems, such as file storage and privacy. In our proposed approach, we will extract the patient's hand motion information and store …

Personalized And Adaptive Semantic Information Filtering For Social Media, Pavan Kapanipathi

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Social media has experienced immense growth in recent times. These platforms are becoming increasingly common for information seeking and consumption, and as part of its growing popularity, information overload pose a significant challenge to users. For instance, Twitter alone generates around 500 million tweets per day and it is impractical for users to have to parse through such an enormous stream to find information that are interesting to them. This situation necessitates efficient personalized filtering mechanisms for users to consume relevant, interesting information from social media. Building a personalized filtering system involves understanding users' interests and utilizing these interests to …

Detecting Php-Based Cross-Site Scripting Vulnerabilities Using Static Program Analysis, Steven M. Kelbley

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With the widespread adoption of dynamic web applications in recent years, a number of threats to the security of these applications have emerged as significant challenges for application developers. The security of developed applications has become a higher priority for both developers and their employers as cyber attacks become increasingly more prevalent and damaging. Some of the most used web application frameworks are written in PHP and have become major targets due to the large number of servers running these applications worldwide. A number of tools exist to evaluate PHP code for issues, however most of these applications are not …

Measures Of User Interactions, Conversations, And Attacks In A Crowdsourced Platform Offering Emotional Support., Samir Yelne

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Online social systems have emerged as a popular medium for people in society to communicate with each other. Among the most important reasons why people communicate is to share emotional problems, but most online social systems are uncomfortable or unsafe spaces for this purpose. This has led to the rise of online emotional support systems, where users needing to speak to someone can anonymously connect to a crowd of trained listeners for a one-on-one conversation. To better understand who, how and when users utilize these systems, and to evaluate their safety, this thesis offers a comprehensive examination of the characteristics …

Towards Best Practices For Crowdsourcing Ontology Alignment Benchmarks, Reihaneh Amini

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Ontology alignment systems establish the semantic links between ontologies that enable knowledge from various sources and domains to be used by automated applications in many different ways. Unfortunately, these systems are not perfect. Currently, the results of even the best-performing automated alignment systems need to be manually verified in order to be fully trusted. Ontology alignment researchers have turned to crowdsourcing platforms such as Amazon's Mechanical Turk to accomplish this. However, there has been little systematic analysis of the accuracy of crowdsourcing for alignment verification and the establishment of best practices. In this work, we analyze the impact of the …

Mining And Analyzing Subjective Experiences In User Generated Content, Lu Chen

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Web 2.0 and social media enable people to create, share and discover information instantly anywhere, anytime. A great amount of this information is subjective information -- the information about people's subjective experiences, ranging from feelings of what is happening in our daily lives to opinions on a wide variety of topics. Subjective information is useful to individuals, businesses, and government agencies to support decision making in areas such as product purchase, marketing strategy, and policy making. However, much useful subjective information is buried in ever-growing user generated data on social media platforms, it is still difficult to extract high quality …

Knowledge-Driven Implicit Information Extraction, Pathirage Dinindu Perera

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Natural language is a powerful tool developed by humans over hundreds of thousands of years. The extensive usage, flexibility of the language, creativity of the human beings, and social, cultural, and economic changes that have taken place in daily life have added new constructs, styles, and features to the language. One such feature of the language is its ability to express ideas, opinions, and facts in an implicit manner. This is a feature that is used extensively in day to day communications in situations such as: 1) expressing sarcasm, 2) when trying to recall forgotten things, 3) when required to …

Identifying Tweets With Implicit Entity Mentions, Adarsh Koruthu Alex

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Social networking sites like Twitter and Facebook have become a significant source of user-generated content in the past decade. Mining of this user-generated content has proved beneficial for a broad range of applications like Event Extraction, Document Retrieval, and Sentiment Analysis. Identifying entities is one of the major tasks that fuel important information for above tasks. Identification of entities is typically performed in two steps; Named Entity Recognition (NER) and Entity Linking. State of the art NER solutions focus on recognizing the entities that are mentioned explicitly in social media posts. However, entities are frequently mentioned implicitly in them. For …

Framework For Semantic Integration And Scalable Processing Of City Traffic Events, Surendra Brahma Marupudi

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Intelligent traffic management requires analysis of a large volume of multimodal data from diverse domains. For the development of intelligent traffic applications, we need to address diversity in observations from physical sensors which give weather, traffic flow, parking information; we also need to do the same with social media, which provides live commentary of various events in a city. The extraction of relevant events and the semantic integration of numeric values from sensors, unstructured text from Twitter, and semi- structured data from city authorities is a challenging physical-cyber-social data integration problem. In order to address the challenge of both scalability …

Miniatured Inertial Motion And Position Tracking And Visualization Systems Using Android Wear Platform, Dhruvkumar Navinchandra Patel

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In this thesis, we have designed and developed a motion tracking and visualization system using the latest motion tracking sensory technologies. It is one of the enabling technologies for our novel visual-inertial odometer and human anatomy based 3D Locating, Mapping and Navigation system for endoscopy and drug delivery capsules used inside GI tract. In particular, we have: i) designed and completed a cloud-based sensory data collecting, processing and storage system to provide the reliable computing and storage platform; ii) explored different data processing methods to obtain improved-quality motion results from extremely noisy raw data, e.g., by using a low pass …

Educational Methods For Inverted-Lecture Computer Science And Engineering Classrooms To Overcome Common Barriers To Stem Student Success, Kathleen Timmerman

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New educational pedagogies are emerging in an effort to increase the number of new engineers available to enter the workforce in the coming years. One of the re-occurring themes in these pedagogies is variations of the flipped classroom. Often the additional classroom time gained from flipping is used to reinforce learning objectives. It is hypothesized that it might be more beneficial to students if a portion of that time is used to address common non-cognitive barriers that prevent students from succeeding in the major. In a freshman Introductory Computer Science course, three different pedagogies are compared: a hybrid lecture-active learning …

De-Anonymization Attack Anatomy And Analysis Of Ohio Nursing Workforce Data Anonymization, Jacob M. Miracle

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Data generalization (anonymization) is a widely misunderstood technique for preserving individual privacy in non-interactive data publishing. Easily avoidable anonymization failures are still occurring 14 years after the discovery of basic techniques to protect against them. Identities of individuals in anonymized datasets are at risk of being disclosed by cyber attackers who exploit these failures. To demonstrate the importance of proper data anonymization we present three perspectives on data anonymization. First, we examine several de-anonymization attacks to formalize the anatomy used to conduct attacks on anonymous data. Second, we examine the vulnerabilities of an anonymous nursing workforce survey to convey how …

A Hybrid Approach To Aerial Video Image Registration, Karol T. Salva

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Many video processing applications, such as motion detection and tracking, rely on accurate and robust alignment between consecutive video frames. Traditional approaches to video image registration, such as pyramidal Kanade-Lucas-Tomasi (KLT) feature detection and tracking are fast and subpixel accurate, but are not robust to large inter-frame displacements due to rotation, scale, or translation. This thesis presents an alternative hybrid approach using normalized gradient correlation (NGC) in the frequency domain and normalized cross-correlation (NCC) in the spatial domain that is fast, accurate, and robust to large displacements. A scale space search is incorporated into NGC to enable more consistent recovery …

Intelligent Caching To Mitigate The Impact Of Web Robots On Web Servers, Howard Nathan Rude

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With an ever increasing amount of data that is shared and posted on the Web, the desire and necessity to automatically glean this information has led to an increase in the sophistication and volume of software agents called web robots or crawlers. Recent measurements, including our own across the entire logs of Wright State University Web servers over the past two years, suggest that at least 60\% of all requests originate from robots rather than humans. Web robots display different statistical and behavioral patterns in their traffic compared to humans, yet present Web server optimizations presume that traffic exhibits predominantly …

Identifying Offensive Videos On Youtube, Rajeshwari Kandakatla

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Harassment on social media has become a critical problem and social media content depicting harassment is becoming common place. Video-sharing websites such as YouTube contain content that may be offensive to certain community, insulting to certain religion, race etc., or make fun of disabilities. These videos can also provoke and promote altercations leading to online harassment of individuals and groups. In this thesis, we present a system that identifies offensive videos on YouTube. Our goal is to determine features that can be used to detect offensive videos efficiently and reliably. We conducted experiments using content and metadata available for each …