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A Performance Analysis Framework For Coreference Resolution Algorithms, Chandankumar Johakhim Patel
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 …
Resqu: A Framework For Automatic Evaluation Of Knowledge-Driven Automatic Summarization, Nishita Jaykumar
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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 …
An Autoencoder-Based Image Descriptor For Image Matching And Retrieval, Chenyang Zhao
An Autoencoder-Based Image Descriptor For Image Matching And Retrieval, Chenyang Zhao
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Local image features are used in many computer vision applications. Many point detectors and descriptors have been proposed in recent years; however, creation of effective descriptors is still a topic of research. The Scale Invariant Feature Transform (SIFT) developed by David Lowe is widely used in image matching and image retrieval. SIFT detects interest points in an image based on Scale-Space analysis, which is invariant to change in image scale. A SIFT descriptor contains gradient information about an image patch centered at a point of interest. SIFT is found to provide a high matching rate, is robust to image transformations; …
Gpu-Accelerated Feature Tracking, Alex Graves
Gpu-Accelerated Feature Tracking, Alex Graves
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The motivation of this research is to prove that GPUs can provide significant speedup of long-executing image processing algorithms by way of parallelization and massive data throughput. This thesis accelerates the well-known KLT feature tracking algorithm using OpenCL and an NVidia GeForce GTX 780 GPU. KLT is a fast, efficient and accurate feature tracker but can easily suffer from low frame rates when tracking many features in an HD video sequence. This research explains how KLT could benefit from GPGPU programming and provides the corresponding OpenCL implementation. Additionally, various optimization techniques are emphasized to further boost GPU performance. The experiments …
A Stochastic Petri Net Based Nlu Scheme For Technical Documents Understanding, Adamantia Psarologou
A Stochastic Petri Net Based Nlu Scheme For Technical Documents Understanding, Adamantia Psarologou
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Natural Language Understanding (NLU) is a very old research field, which deals with machine reading comprehension. Despite the many years of work and the numerous accomplishments by several researchers in the field, there is still place for significant improvements. Here, our goal is to develop a novel NLU methodology for detecting and extracting event/action associations in technical documents. In order to achieve this goal we present a synergy of methods (Kernel extraction, Formal Language Modeling, Stochastic Petri-nets (SPN) mapping and Event Representation via SPN graph synthesis). In particular, the basic meaning of a natural language sentence is given by its …
Software Defined Secure Ad Hoc Wireless Networks, Maha Alqallaf
Software Defined Secure Ad Hoc Wireless Networks, Maha Alqallaf
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Software defined networking (SDN), a new networking paradigm that separates the network data plane from the control plane, has been considered as a flexible, layered, modular, and efficient approach to managing and controlling networks ranging from wired, infrastructure-based wireless (e.g., cellular wireless networks, WiFi, wireless mesh net- works), to infrastructure-less wireless networks (e.g. mobile ad-hoc networks, vehicular ad-hoc networks) as well as to offering new types of services and to evolving the Internet architecture. Most work has focused on the SDN application in traditional and wired and/or infrastructure based networks. Wireless networks have become increasingly more heterogeneous. Secure and collab- …
Knowledge-Empowered Probabilistic Graphical Models For Physical-Cyber-Social Systems, Pramod Anantharam
Knowledge-Empowered Probabilistic Graphical Models For Physical-Cyber-Social Systems, Pramod Anantharam
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There is a rapid intertwining of sensors and mobile devices into the fabric of our lives. This has resulted in unprecedented growth in the number of observations from the physical and social worlds reported in the cyber world. Sensing and computational components embedded in the physical world constitute a Cyber-Physical System (CPS). Current science of CPS is yet to effectively integrate citizen observations in CPS analysis. We demonstrate the role of citizen observations in CPS and propose a novel approach to perform a holistic analysis of machine and citizen sensor observations. Specifically, we demonstrate the complementary, corroborative, and timely aspects …
Knowledge Driven Search Intent Mining, Ashutosh Jadhav
Knowledge Driven Search Intent Mining, Ashutosh Jadhav
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Understanding users' latent intents behind search queries is essential for satisfying a user's search needs. Search intent mining can help search engines to enhance its ranking of search results, enabling new search features like instant answers, personalization, search result diversification, and the recommendation of more relevant ads. Hence, there has been increasing attention on studying how to effectively mine search intents by analyzing search engine query logs. While state-of-the-art techniques can identify the domain of the queries (e.g. sports, movies, health), identifying domain-specific intent is still an open problem. Among all the topics available on the Internet, health is one …