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Full-Text Articles in Computer Engineering
Domain-Specific Knowledge Extraction From The Web Of Data, Sarasi Lalithsena
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 …
Measuring Goal Similarity Using Concept, Context And Task Features, Vahid Eyorokon
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 said …
A Twitter-Based Study For Understanding Public Reaction On Zika Virus, Roopteja Muppalla
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 precautions …
Virtual Doctor: An Intelligent Human-Computer Dialogue System For Quick Response To People In Need, Stavros Mallios
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, …
Implementation Of Unmanned Aerial Vehicles Reporting Plume Cloud Concentration Values In A 3d Simulation Environment, Emily Catherine Novak
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 plume …
Slim Embedding Layers For Recurrent Neural Language Models, Zhongliang Li
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 …
Threats And Mitigation Of Ddos Cyberattacks Against The U.S. Power Grid Via Ev Charging, Glenn Sean Morrison
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 …
Use Of Adaptive Mobile Applications To Improve Mindfulness, Wiehan Boshoff
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 …
Developing A Kinect Based Holoportation System, Soumya Chiday
Developing A Kinect Based Holoportation System, Soumya Chiday
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Holographic communication and distributed collaboration offer great potential for empathic computing to help remove the cost, distance, language and expertise barriers in many social and economic activities. Recent advances in AR-enhanced communication as evident by Microsoft Holoportation technology demonstrate the progress toward fully immersive collaborations distributed and remotely. Current holoportation system requires the use of extensive camera-arrays and powerful server system due to the computation demand and sensory needs to capture and reconstruct the subject of interests Thus, they suffer in mobility and applicability in real-world scenarios. In this thesis, we present an ultra-portable holoportation system design that requires only …
Augment The Multi-Modal Interaction Capabilities Of Hololens Through Networked Sensory Devices, Subhadra Tummalapally
Augment The Multi-Modal Interaction Capabilities Of Hololens Through Networked Sensory Devices, Subhadra Tummalapally
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Augmented Reality (AR) places virtual contents along with real objects to enhance user perception in the physical environment. It is a technology that has shown great potential in many industries such as medicine, education and transportation. AR devices, such as Microsoft HoloLens, come with multi-modal interaction capabilities, such as voice, gesture and gaze, to support intuitive and reliable human-computer interactions. However, HoloLens gesture support is limited to simple gestures like tap, bloom and hold, it stops short to support meaningful interaction through full hand gesture and motion tracking, which may be critical in field operations of various industry practices in …
Using Natural Language Processing And Machine Learning For Analyzing Clinical Notes In Sickle Cell Disease Patients, Shufa Khizra
Using Natural Language Processing And Machine Learning For Analyzing Clinical Notes In Sickle Cell Disease Patients, Shufa Khizra
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Sickle Cell Disease (SCD) is a hereditary disorder in red blood cells that can lead to excruciating pain episodes. SCD causes the normal red blood cells to distort its shape and turn into sickle shape. The distorted shape makes the hemoglobin inflexible and stick to the walls of the vessels thereby obstructing the free flow of blood and eventually making the tissues suffer from lack of oxygen. The lack of oxygen causes serious problems including Acute Chest Syndrome (ACS), stroke, infection, organ damage, and over the lifetime an SCD can harm a persons spleen, brain, kidneys, eyes, bones. Sickling of …
Multi-Scale And Multi-Modal Streaming Data Aggregation And Processing For Decision Support During Natural Disasters, Shruti Kar
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With the surge in digital information systems, there is a data deluge from various sources that can be analyzed and integrated to produce relevant, reliable and actionable information, for better decision making. We employ multi-modal data (i.e., unstructured text, gazetteers, and imagery) for an aggregate level analysis and location-centric demand/request matching in the context of disaster relief. After classifying the Need expressed in a tweet (the WHAT), we leverage OpenStreetMap to geolocate that Need on a computationally accessible map of the local terrain (the WHERE) populated with location features such as hospitals and housing. Further, our novel use of flood …
A Model For Seasonal Dynamic Networks, Jace D. Robinson
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 …
Content-Based Clustering And Visualization Of Social Media Text Messages, Sydney A. Barnard
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 Multi-Formal Languages Collaborative Scheme For Complex Human Activity Recognition And Behavioral Patterns Extraction, Anargyros Angeleas
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 …
A Stochastic Petri Net Reverse Engineering Methodology For Deep Understanding Of Technical Documents, Giorgia Rematska
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 …
Development Of An Ios App For Learning Intonation Of Wind Instruments, Swathi Pamidi
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 - …
Malware Analysis Skills Taught In University Courses, Swetha Gorugantu
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 …
Sensor Data Streams Correlation Platform For Asthma Management, Vaikunth Sridharan
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
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. The current …
Building An Abstract-Syntax-Tree-Oriented Symbolic Execution Engine For Php Programs, Jin Huang
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, …
Verifying Data-Oriented Gadgets In Binary Programs To Build Data-Only Exploits, Zachary David Sisco
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 introduces difficulties …
Image Stitching And Matching Tool In The Automated Iterative Reverse Engineer (Aire) Integrated Circuit Analysis Suite, David C. Bowman
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 …
The Feasibility Of Dementia Caregiver Task Performance Measurement Using Smart Gaming Technology, Garrett G. Goodman
The Feasibility Of Dementia Caregiver Task Performance Measurement Using Smart Gaming Technology, Garrett G. Goodman
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Dementia caregiver burnout is detrimental to both the familial caregiver and their loved ones with dementia. As the population of older adults increases, both the number of individuals with dementia and their corresponding caregivers increase as well. Thus, we are interested in developing a potential tool to non-invasively detect signs of caregiver burnout using a mobile application combined with machine learning. Hence, the mobile application "Caregiver Assessment using Smart Technology" (CAST) was developed which personalizes a word scramble game. The CAST application utilizes a heuristically constructed Fuzzy Inference System (FIS) optimized via a Genetic Algorithm (GA) to provide an individualized …
Interactive Visualization Of Search Results Of Large Document Sets, James D. Anderson
Interactive Visualization Of Search Results Of Large Document Sets, James D. Anderson
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When presented with many search results, finding information or patterns within the data poses a challenge. This thesis presents the design, implementation and evaluation of a visualization enabling users to browse through voluminous information and comprehend the data. Implemented with the JavaScript library Data Driven Documents (D3), the visualization represents the search as clusters of similar documents grouped into bubbles with the contents depicted as word-clouds. Highly interactive features such as touch gestures and intuitive menu actions allow for expeditious exploration of the search results. Other features include drag-and-drop functionality for articles among bubbles, merging nodes, and refining the search …
Development Of A Human-Ai Teaming Based Mobile Language Learning Solution For Dual Language Learners In Early And Special Educations, Saurabh Shukla
Development Of A Human-Ai Teaming Based Mobile Language Learning Solution For Dual Language Learners In Early And Special Educations, Saurabh Shukla
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Learning English as a secondary language is often an overwhelming challenge for dual language learners (DLLs), whose first language (L1) is not English, especially for children in early education (PreK-3 age group). These early DLLs need to devote a considerable amount of time learning to speak and read the language, in order to gain the language proficiency to function and compete in the classroom. Fear of embarrassment when mispronouncing words in front of others may drive them to remain silent; effectively hampering their participation in the class and overall curricular growth. The process of learning a new language can benefit …
Overwhelming The Saa System Of Delivery Uavs By Drone Swarming, Barry Lynn Pfaff
Overwhelming The Saa System Of Delivery Uavs By Drone Swarming, Barry Lynn Pfaff
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As the Internet continues to replace the brick-and-mortar store as the main place for purchasing goods, web-based companies are looking for ways to reduce the cost of delivering those goods. The use of Unmanned Aerial Vehicles, or UAVs, is one delivery method that is increasingly being used. These UAVs can be programmed with delivery routes and destinations and can complete the job while requiring limited intervention from human controllers. Sense and Avoidance (SAA) systems have recently been incorporated into these UAVs so that they can detect objects in their flight path, reroute the UAV accordingly and operate even more autonomously. …
Multiple Drone Detection And Acoustic Scene Classification With Deep Learning, Hari Charan Vemula
Multiple Drone Detection And Acoustic Scene Classification With Deep Learning, Hari Charan Vemula
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Classification of environmental scenes and detection of events in one's environment from audio signals enables one to create better-planning agents, intelligent navigation systems, pattern recognition systems, and audio surveillance systems. This thesis will explore the use of Convolutional Neural Networks(CNN'S) with spectrograms and raw audio waveforms as inputs to Deep Neural Networks with hand engineered features extracted from large-scale feature extraction schemes to identify the acoustic scenes and events. The first part focuses on building an audio pattern recognition system capable of detecting the if there are zero, one, or two DJI phantoms in the scene within the range of …
Fully Transparent Computer Vision Framework For Ship Detection And Tracking In Satellite Imagery, Jason T. Gottweis
Fully Transparent Computer Vision Framework For Ship Detection And Tracking In Satellite Imagery, Jason T. Gottweis
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Tracking of ships in satellite imagery is a challenging problem in remote sensing since it requires both object detection and object recognition. Most of the resources available only cover one of these problems and are often filled with machine learning techniques which are costly to train. Additionally, the techniques covered in these resources are often difficult to replicate or may be hard to combine with other solutions to get a full tracking algorithm. The proposed framework offers a transparent and efficient alternative to machine learning approaches and includes preprocessing, detection, and recognition needed for tracking. All components of the framework …