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Department of Computer Science and Engineering

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Threats And Mitigation Of Ddos Cyberattacks Against The U.S. Power Grid Via Ev Charging, Glenn Sean Morrison Jan 2018

Threats And Mitigation Of Ddos Cyberattacks Against The U.S. Power Grid Via Ev Charging, Glenn Sean Morrison

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Cars are an ever changing and integral part of modern society. Two of the biggest changes in vehicles today are their heavy integration with wireless communication and the push toward battery powered Electric Vehicles (EV). EV and EV charging stations have become a part of the Internet of Things (IoT). While this connectedness increases the convenience and functionality of the vehicles and charging stations, it also opens them up to a wide range of cyber threats. This thesis examines the potential threats against the EV charging ecosystem through a historical analysis of past cyberattacks and identified vulnerabilities. As EV charging ...


A Twitter-Based Study For Understanding Public Reaction On Zika Virus, Roopteja Muppalla Jan 2018

A Twitter-Based Study For Understanding Public Reaction On Zika Virus, Roopteja Muppalla

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In recent times, social media platforms like Twitter have become more popular and people have become more interactive and responsive than before. People often react to every news in real-time and within no-time, the information spreads rapidly. Even with viral diseases like Zika, people tend to share their opinions and concerns on social media. This can be leveraged by the health officials to track the disease in real-time thereby reducing the time lag due to traditional surveys. A faster and accurate detection of the disease can allow health officials to understand people's opinion of the disease and take necessary ...


A Model For Seasonal Dynamic Networks, Jace D. Robinson Jan 2018

A Model For Seasonal Dynamic Networks, Jace D. Robinson

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Sociotechnological and geospatial processes exhibit time varying structure that make insight discovery challenging. This paper presents statistical model of systems with seasonal dynamics, modeled as a dynamic network, to address this challenge. It assumes the probability of edge formations depend on a type assigned to incident nodes and the current time. Time dependencies are modeled by unique seasonal processes. The model is studied on several synthetic and real datasets. Superior fidelity of this model on seasonal datasets compared to existing network models, while being able to remain equally accurate for networks with randomly changing structure, is shown. The model is ...


Virtual Doctor: An Intelligent Human-Computer Dialogue System For Quick Response To People In Need, Stavros Mallios Jan 2018

Virtual Doctor: An Intelligent Human-Computer Dialogue System For Quick Response To People In Need, Stavros Mallios

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One of the challenges of our society is the existence of chronic-related conditions and diseases among the elderly and people at risk. Apart from the welfare of people, a significant impact of this phenomenon is the accumulation of high financial costs for both individuals and health care systems. In order to address this issue and to reduce its effects, many efforts have been made towards preventing, identifying in early stages and, generally, managing chronic-related medical conditions and diseases. As a result, there has been a keen research and market interest in health monitoring devices during the past few decades. Nevertheless ...


Content-Based Clustering And Visualization Of Social Media Text Messages, Sydney A. Barnard Jan 2018

Content-Based Clustering And Visualization Of Social Media Text Messages, Sydney A. Barnard

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Although Twitter has been around for more than ten years, crisis management agencies and first response personnel are not able to fully use the information this type of data provides during a crisis or natural disaster. This thesis addresses clustering and visualizing social media data by textual similarity, rather than by only time and location, as a tool for first responders. This thesis presents a tool that automatically clusters geotagged text data based on their content and displays the clusters and their locations on the map. It allows at-a-glance information to be displayed throughout the evolution of a crisis. For ...


A Stochastic Petri Net Reverse Engineering Methodology For Deep Understanding Of Technical Documents, Giorgia Rematska Jan 2018

A Stochastic Petri Net Reverse Engineering Methodology For Deep Understanding Of Technical Documents, Giorgia Rematska

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Systems Reverse Engineering has gained great attention over time and is associated with numerous different research areas. The importance of this research derives from several technological necessities. Security analysis and learning purposes are two of them and can greatly benefit from reverse engineering. More specifically, reverse engineering of technical documents for deeper automatic understanding is a research area where reverse engineering can contribute a lot. In this PhD dissertation we develop a novel reverse engineering methodology for deep understanding of architectural description of digital hardware systems that appear in technical documents. Initially, we offer a survey on reverse engineering of ...


A Multi-Formal Languages Collaborative Scheme For Complex Human Activity Recognition And Behavioral Patterns Extraction, Anargyros Angeleas Jan 2018

A Multi-Formal Languages Collaborative Scheme For Complex Human Activity Recognition And Behavioral Patterns Extraction, Anargyros Angeleas

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Human Activity Recognition is an actively researched domain for the past few decades, and is one of the most eminent applications of today. It is already part of our life, but due to high level of uncertainty and challenges of human detection, we have only application specific solutions. Thus, the problem being very demanding and still remains unsolved. Within this PhD we delve into the problem, and approach it from a variety of viewpoints. At start, we present and evaluate different architectures and frameworks for activity recognition. Henceforward, the focal point of our attention is automatic human activity recognition. We ...


Implementation Of Unmanned Aerial Vehicles Reporting Plume Cloud Concentration Values In A 3d Simulation Environment, Emily Catherine Novak Jan 2018

Implementation Of Unmanned Aerial Vehicles Reporting Plume Cloud Concentration Values In A 3d Simulation Environment, Emily Catherine Novak

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Unmanned aerial vehicles, or UAVs, have the potential to vastly improve plume cloud tracking at low cost. Plume clouds can be produced from blast mining, chemical warfare, unintended man-made disasters, and natural causes. This thesis provides implementation of the capability to simulate a 3D environment in which UAVs are individually controlled and each report a plume's concentration value at a specific location. It leverages existing industry standard technologies, including the PX4 autopilot system, the Gazebo simulation environment, the Robot Operating System (ROS), and QGroundControl. The provided system integrates the existing tools with a plume model plug-in that provides simulated ...


Development Of An Ios App For Learning Intonation Of Wind Instruments, Swathi Pamidi Jan 2018

Development Of An Ios App For Learning Intonation Of Wind Instruments, Swathi Pamidi

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Learning music instrument is a challenging task for a beginner without constant guidance from an instructor. The primary objective of this thesis research is to design and develop an iOS mobile / iPad learning app that helps users to learn and practice intonation for a suite of wind instruments by themselves with comfort and ease through app-provided tuning and charting guidance and app-assisted self-assessment. Particularly, our successfully-implemented app provides the following features to enhance the user's learning experience: 1 ) Provides learners easy-to-access information for the fingering and tuning techniques of wind instruments by converting Dr. Shelley Jagow's book - "Tuning ...


Domain-Specific Knowledge Extraction From The Web Of Data, Sarasi Lalithsena Jan 2018

Domain-Specific Knowledge Extraction From The Web Of Data, Sarasi Lalithsena

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Domain knowledge plays a significant role in powering a number of intelligent applications such as entity recommendation, question answering, data analytics, and knowledge discovery. Recent advances in Artificial Intelligence and Semantic Web communities have contributed to the representation and creation of this domain knowledge in a machine-readable form. This has resulted in a large collection of structured datasets on the Web which is commonly referred to as the Web of data. The Web of data continues to grow rapidly since its inception, which poses a number of challenges in developing intelligent applications that can benefit from its use. Majority of ...


Slim Embedding Layers For Recurrent Neural Language Models, Zhongliang Li Jan 2018

Slim Embedding Layers For Recurrent Neural Language Models, Zhongliang Li

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Recurrent neural language (RNN) models are the state-of-the-art method for language modeling. When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of these type of models. We introduce a simple space compression method that stochastically shares the structured parameters at both the input and output embedding layers of RNN models to significantly reduce the size of model parameters, but still compactly represents the original input and the output embedding layers. The method is easy to implement and tune. Experiments on several data sets show that the new method achieves ...


Verifying Data-Oriented Gadgets In Binary Programs To Build Data-Only Exploits, Zachary David Sisco Jan 2018

Verifying Data-Oriented Gadgets In Binary Programs To Build Data-Only Exploits, Zachary David Sisco

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Data-Oriented Programming (DOP) is a data-only code-reuse exploit technique that "stitches" together sequences of instructions to alter a program's data flow to cause harm. DOP attacks are difficult to mitigate because they respect the legitimate control flow of a program and by-pass memory protection schemes such as Address Space Layout Randomization, Data Execution Prevention, and Control Flow Integrity. Techniques that describe how to build DOP payloads rely on a program's source code. This research explores the feasibility of constructing DOP exploits without source code-that is, using only binary representations of programs. The lack of semantic and type information ...


Image Stitching And Matching Tool In The Automated Iterative Reverse Engineer (Aire) Integrated Circuit Analysis Suite, David C. Bowman Jan 2018

Image Stitching And Matching Tool In The Automated Iterative Reverse Engineer (Aire) Integrated Circuit Analysis Suite, David C. Bowman

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Due to current market forces, leading-edge semiconductor fabrication plants have moved outside of the US. While this is not a problem at first glance, when it comes to security-sensitive applications, over-production, device cloning, or design alteration becomes a possibility. Since these vulnerabilities exist during the fabrication phase, a Reverse Engineering (RE) step must be introduced to help ensure secure device operation. This thesis proposes several unique methods and a collection of tools to ensure trust assurance in integrated circuit design by detecting fabrication flaws and possible hardware Trojans using several image processing techniques; fused into a singular view of the ...


Measuring Goal Similarity Using Concept, Context And Task Features, Vahid Eyorokon Jan 2018

Measuring Goal Similarity Using Concept, Context And Task Features, Vahid Eyorokon

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Goals can be described as the user's desired state of the agent and the world and are satisfied when the agent and the world are altered in such a way that the present state matches the desired state. For physical agents, they must act in the world to alter it in a series of individual atomic actions. Traditionally, agents use planning to create a chain of actions each of which altering the current world state and yielding a new one until the final action yields the desired goal state. Once this goal state has been achieved, the goal is ...


Malware Analysis Skills Taught In University Courses, Swetha Gorugantu Jan 2018

Malware Analysis Skills Taught In University Courses, Swetha Gorugantu

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Career opportunities for malware analysts are growing at a fast pace due to the evolving nature of cyber threats as well as the necessity to counter them. However, employers are often unable to hire analysts fast though due to a lack of the required skillset. Hence, the primary purpose of the thesis is to conduct a gap analysis between the binary analysis skills taught in universities with those that the recruiters are looking for. Malware can be analyzed using three main types of tools and techniques: high-level profiling, static analysis, and dynamic analysis. These methods provide detailed information about the ...


Use Of Adaptive Mobile Applications To Improve Mindfulness, Wiehan Boshoff Jan 2018

Use Of Adaptive Mobile Applications To Improve Mindfulness, Wiehan Boshoff

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Mindfulness is the state of retaining awareness of what is happening at the current point in time. It has been used in multiple forms to reduce stress, anxiety, and even depression. Promoting Mindfulness can be done in various ways, but current research shows a trend towards preferential usage of breathing exercises over other methods to reach a mindful state. Studies have showcased that breathing can be used as a tool to promote brain control, specifically in the auditory cortex region. Research pertaining to disorders such as Tinnitus, the phantom awareness of sound, could potentially benefit from using these brain control ...


Sensor Data Streams Correlation Platform For Asthma Management, Vaikunth Sridharan Jan 2018

Sensor Data Streams Correlation Platform For Asthma Management, Vaikunth Sridharan

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Asthma is a high-burden chronic inflammatory disease with prevalence in children with twice the rate compared to adults. It can be improved by continuously monitoring patients and their environment using the Internet of Things (IoT) based devices. These sensor data streams so obtained are essential to comprehend multiple factors triggering asthma symptoms. In order to support physicians in exploring causal associations and finding actionable insights, a visualization system with a scalable cloud infrastructure that can process multimodal sensor data and Patient Generated Health Data (PGHD) is necessary. In this thesis, we describe a cloud-based asthma management and visualization platform that ...


A Semantically Enhanced Approach To Identify Depression-Indicative Symptoms Using Twitter Data, Ankita Saxena Jan 2018

A Semantically Enhanced Approach To Identify Depression-Indicative Symptoms Using Twitter Data, Ankita Saxena

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According to the World Health Organization, more than 300 million people suffer from Major Depressive Disorder (MDD) worldwide. PHQ-9 is used to screen and diagnose MDD clinically and identify its severity. With the unprecedented growth and enthusiastic acceptance of social media such as Twitter, a large number of people have come to share their feelings and emotions on it openly. Each tweet can indicate a user's opinion, thought or feeling. A tweet can also indicate multiple symptoms related to PHQ-9. Identifying PHQ-9 symptoms indicated by a tweet can provide crucial information about a user regarding his/her depression diagnosis ...


Building An Abstract-Syntax-Tree-Oriented Symbolic Execution Engine For Php Programs, Jin Huang Jan 2018

Building An Abstract-Syntax-Tree-Oriented Symbolic Execution Engine For Php Programs, Jin Huang

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This thesis presents the design, implementation, and evaluation of an abstract-syntax-tree-oriented symbolic execution engine for the PHP programming language. As a symbolic execution engine, our system emulate the execution of a PHP program by assuming that all inputs are with symbolic rather than concrete values. While our system inherits the basic definition of symbolic execution, it fundamentally differs from existing symbolic execution implementations that mainly leverage intermediate representation (IRs) to operate. Specifically, our system directly takes the abstract syntax tree (AST) of a program as input and subsequently interprets this AST. Performing symbolic execution using AST offers unique advantages. First ...


Virtuo-Its: An Interactive Tutoring System To Teach Virtual Memory Concepts Of An Operating System, Venkata Krishna Kanth Musunuru Jan 2017

Virtuo-Its: An Interactive Tutoring System To Teach Virtual Memory Concepts Of An Operating System, Venkata Krishna Kanth Musunuru

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Interactive tutoring systems are software applications that help individuals to learn difficult concepts. They can allow students to interact with ideas from essential mathematics to more complicated subjects like software engineering. This thesis concentrates on one such interactive tutoring system (ITS) designed for teaching concepts related to operating system virtual memory. Operating system concepts can be troublesome to learn without having someone or something to explain them. Even when an instructor is able to provide detailed explanations, it is still exceptionally difficult for students without a computer science foundation to comprehend these concepts. Students require a sophisticated set of mental ...


Automated Rendering Of Schema Diagram For Ontologies, Nazifa Karima Jan 2017

Automated Rendering Of Schema Diagram For Ontologies, Nazifa Karima

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Semantic Web extends the current web, using ontologies, metadata and other technologies to establish links between terms and concepts. This enables machines to automatically integrate information across different platforms utilizing the standard definitions. Furthermore, reasoning agents can infer new knowledge by gathering existing information and these additional connections between them. As a result of being designed and maintained independently, data sources exhibit highly heterogeneous nature. This increases the complexity of data integration and hinders interoperability. However, if we can align the overlapping concepts among different domains of knowledge, the prospect of achieving interoperability and integration without having any intermediate reasoning ...


Model Preparation And User Interface Aspects For Microsoft Hololens Medical Tutorial Applications, Andrew J. Mcnutt Jan 2017

Model Preparation And User Interface Aspects For Microsoft Hololens Medical Tutorial Applications, Andrew J. Mcnutt

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Augmented Reality (AR) is the combination of computer vision and graphics to allow a device to derive context about the environment and to display relevant information to the user. The Microsoft Hololens is the latest wearable AR device that includes a series of infrared sensors to perform hand tracking and Simultaneous Localization and Mapping, a wave guide optics system to project holograms, and an independent untethered operating system. This thesis will explore the hardware and software capabilities of the device, prepare 3D graphical models, and understand the user interface. Specifically, in our research the target application is a tutorial on ...


Development Of An Android Based Performance Assessment System For Motivational Interviewing Training, Sowmya Pappu Jan 2017

Development Of An Android Based Performance Assessment System For Motivational Interviewing Training, Sowmya Pappu

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Motivational Interviewing (MI) has been proved to be an effective Screening, Brief Intervention, and Referral to Treatment (SBIRT) technique. It is an evidence-based practice used to identify, reduce, and prevent problematic use, abuse, and dependence on alcohol and illicit drugs. It emphasizes on patient-centered counseling approach that can help resolve their ambivalence through a non-confrontational, goal-oriented style for eliciting behavior change from the patient, almost like patients talk themselves into change. This approach provokes less resistance and stimulates the progress of patients at their own pace towards deciding about planning, making and sustaining positive behavioral change. Thus, training medical professionals ...


Efficient Reasoning Algorithms For Fragments Of Horn Description Logics, David Carral Jan 2017

Efficient Reasoning Algorithms For Fragments Of Horn Description Logics, David Carral

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We characterize two fragments of Horn Description Logics and we define two specialized reasoning algorithms that effectively solve the standard reasoning tasks over each of such fragments. We believe our work to be of general interest since (1) a rather large proportion of real-world Horn ontologies belong to some of these two fragments and (2) the implementations based on our reasoning approach significantly outperform state-of-the-art reasoners. Claims (1) and (2) are extensively proven via empirically evaluation.


Harassment Detection On Twitter Using Conversations, Venkatesh Edupuganti Jan 2017

Harassment Detection On Twitter Using Conversations, Venkatesh Edupuganti

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Social media has brought people closer than ever before, but the use of social media has also brought with it a risk of online harassment. Such harassment can have a serious impact on a person such as causing low self-esteem and depression. The past research on detecting harassment on social media is primarily based on the content of messages exchanged on social media. The lack of context when relying on a single social media post can result in a high degree of false alarms. In this study, I focus on the reliable detection of harassment on Twitter by better understanding ...


Detection Of Ddos Attacks Against The Sdn Controller Using Statistical Approaches, Basheer Husham Ali Al-Mafrachi Jan 2017

Detection Of Ddos Attacks Against The Sdn Controller Using Statistical Approaches, Basheer Husham Ali Al-Mafrachi

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In traditional networks, switches and routers are very expensive, complex, and inflexible because forwarding and handling of packets are in the same device. However, Software Defined Networking (SDN) makes networks design more flexible, cheaper, and programmable because it separates the control plane from the data plane. SDN gives administrators of networks more flexibility to handle the whole network by using one device which is the controller. Unfortunately, SDN faces a lot of security problems that may severely affect the network operations if not properly addressed. Threat vectors may target main components of SDN such as the control plane, the data ...


Portable Motion Lab For Diagnostic And Rehabilitation Processes, Yogesh Laxman Chavan Jan 2017

Portable Motion Lab For Diagnostic And Rehabilitation Processes, Yogesh Laxman Chavan

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In this thesis research, we have explored the capabilities of a household body-tracking device - Microsoft Xbox Kinect for motion analysis and assessment to assist patient’s rehabilitation after joint replacement and repair surgeries. In particular, we have combined the motion tracking capabilities of Kinect with the 3D modelling of human body for accurate and intuitive movement assessment and feedback. Our prototype system demonstrates the effective and efficient workflow of motion capturing, data processing and analyzing and augmented reality based presentation, resulting in a design which is not only accurate, reliable and robust, but also extremely cost- and space-efficient. Furthermore, we ...


Characterizing Concepts In Taxonomy For Entity Recommendations, Siva Kumar Cheekula Jan 2017

Characterizing Concepts In Taxonomy For Entity Recommendations, Siva Kumar Cheekula

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Entity recommendation systems are enormously popular on the Web. These systems harness manually crafted taxonomies for improving recommendations. For example, Yahoo created the Open Directory Project for search and recommendation, and Amazon utilizes its own product taxonomy. While these taxonomies are of high quality, it is a labor and time-intensive process to manually create and keep them up to date. Instead, in this era ofWeb 2.0 where users collaboratively create large amounts of information on the Web, it is possible to utilize user-generated content to automatically generate good quality taxonomies. However, harnessing such taxonomies for entity recommendations has not ...


Distance Learning And Attribute Importance Analysis By Linear Regression On Idealized Distance Functions, Rupesh Kumar Singh Jan 2017

Distance Learning And Attribute Importance Analysis By Linear Regression On Idealized Distance Functions, Rupesh Kumar Singh

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A good distance metric is instrumental on the performance of many tasks including classification and data retrieval. However, designing an optimal distance function is very challenging, especially when the data has high dimensions.Recently, a number of algorithms have been proposed to learn an optimal distance function in a supervised manner, using data with class labels. In this thesis we proposed methods to learn an optimal distance function that can also indicate the importance of attributes. Specifically, we present several ways to define idealized distance functions, two of which involving distance error correction involving KNN classification, and another involving a ...


Sched-Its: An Interactive Tutoring System To Teach Cpu Scheduling Concepts In An Operating Systems Course, Bharath Kumar Koya Jan 2017

Sched-Its: An Interactive Tutoring System To Teach Cpu Scheduling Concepts In An Operating Systems Course, Bharath Kumar Koya

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Operating systems is an essential course in computer science curriculum, which helps students to develop a mental model of how computer operating systems work. The internal mechanisms and processes of an operating system (OS) are often complex, non-deterministic and intangible which makes them difficult for students to understand. One such concept is central processing unit (CPU) scheduling. CPU scheduling forms the basis of the multiprogramming in an OS. In practice, OS courses involve classroom lectures describing high-level abstractions of the concepts, and students complete programming assignments to apply the material in a more concrete way. Depending on the programming assignments ...