Open Access. Powered by Scholars. Published by Universities.®

Computer Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 30 of 1519

Full-Text Articles in Computer Engineering

Securing Modern Cyberspace Using A Multi-Faceted Approach, Yu Li Jan 2019

Securing Modern Cyberspace Using A Multi-Faceted Approach, Yu Li

Browse all Theses and Dissertations

Security has become one of the most significant concerns for our cyberspace. Securing the cyberspace, however, becomes increasingly challenging. This can be attributed to the rapidly growing diversities and complexity of the modern cyberspace. Specifically, it is not any more dominated by connected personal computers (PCs); instead, it is greatly characterized by cyber-physical systems (CPS), embedded systems, dynamic services, and human-computer interactions. Securing modern cyberspace therefore calls for a multi-faceted approach capable of systematically integrating these emerging characteristics. This dissertation presents our novel and significant solutions towards this direction. Specifically, we have devised automated, systematic security solutions to three critical ...


Kbot: Knowledge-Enabled Personalized Chatbot For Self-Management Of Asthma In Pediatric Population, Dipesh Kadariya Jan 2019

Kbot: Knowledge-Enabled Personalized Chatbot For Self-Management Of Asthma In Pediatric Population, Dipesh Kadariya

Browse all Theses and Dissertations

Asthma, chronic pulmonary disease, is one of the major health issues in the United States. Given its chronic nature, the demand for continuous monitoring of patient’s adherence to the medication care plan, assessment of their environment triggers, and management of asthma control level can be challenging in traditional clinical settings and taxing on clinical professionals. A shift from a reactive to a proactive asthma care can improve health outcomes and reduce expenses. On the technology spectrum, smart conversational systems and Internet-of-Things (IoTs) are rapidly gaining popularity in the healthcare industry. By leveraging such technological prevalence, it is feasible to ...


Speech Enabled Navigation In Virtual Environments, Raksha Rajashekar Jan 2019

Speech Enabled Navigation In Virtual Environments, Raksha Rajashekar

Browse all Theses and Dissertations

Navigating in a Virtual Environment with traditional input devices such as mouse, joysticks and keyboards provide limited maneuverability and is also time consuming. While working in a virtual environment, changing parameters to obtain the desired visualization requires time to achieve by manually entering parameter values in an algorithm to test outcomes. The following thesis presents an alternate user interface to reduce user efforts, while navigating within the Virtual Environment. The user interface is an Android application which is designed to accommodate spoken commands. This Speech Enabled User Interface termed as the Speech Navigation Application (SNA), provides the user with an ...


Towards Data And Model Confidentiality In Outsourced Machine Learning, Sagar Sharma Jan 2019

Towards Data And Model Confidentiality In Outsourced Machine Learning, Sagar Sharma

Browse all Theses and Dissertations

With massive data collections and needs for building powerful predictive models, data owners may choose to outsource storage and expensive machine learning computations to public cloud providers (Cloud). Data owners may choose cloud outsourcing due to the lack of in-house storage and computation resources or the expertise of building models. Similarly, users, who subscribe to specialized services such as movie streaming and social networking, voluntarily upload their data to the service providers' site for storage, analytics, and better services. The service provider, in turn, may also choose to benefit from ubiquitous cloud computing. However, outsourcing to a public cloud provider ...


Detecting Malicious Behavior In Openwrt With Qemu Tracing, Jeremy Porter Jan 2019

Detecting Malicious Behavior In Openwrt With Qemu Tracing, Jeremy Porter

Browse all Theses and Dissertations

In recent years embedded devices have become more ubiquitous than ever before and are expected to continue this trend. Embedded devices typically have a singular or more focused purpose, a smaller footprint, and often interact with the physical world. Some examples include routers, wearable heart rate monitors, and thermometers. These devices are excellent at providing real time data or completing a specific task quickly, but they lack many features that make security issues more obvious. Generally, Embedded devices are not easily secured. Malware or rootkits in the firmware of an embedded system are difficult to detect because embedded devices do ...


Virtual Reality And Analysis Framework For Studying Different Layout Designs, Madison Glines Jan 2019

Virtual Reality And Analysis Framework For Studying Different Layout Designs, Madison Glines

Browse all Theses and Dissertations

This thesis describes the tools for studying different design prototypes. The goal was to develop effective tools to study these designs using a data-driven approach. “Proof of concept” experiments were conducted, in which participants were allowed to interact with a virtual environment depicting different designs as data pertaining to their virtual location and orientation was recorded for later analysis. The designs included “flat” store racks, as opposed to racks with more varied shapes, as well as “curved” racks. Focus of the design studies was to assist in identifying optimal locations for different product types. The automated data collection mechanisms required ...


Llvm-Ir Based Decompilation, Ilsoo Jeon Jan 2019

Llvm-Ir Based Decompilation, Ilsoo Jeon

Browse all Theses and Dissertations

Decompilation is a process of transforming an executable program into a source-like high-level language code, which plays an important role in malware analysis, and vulnerability detection. In this thesis, we design and implement the middle end of a decompiler framework, focusing on Low Level Language properties reduction using the optimization techniques, propagation and elimination. An open-source software tool, dagger, is used to translate binary code to LLVM (Low Level Virtual Machine) Intermediate Representation code. We perform data flow analysis and control flow analysis on the LLVM format code to generate high-level code using a Functional Programming Langauge (FPL), Haskell. The ...


Anticipation In Dynamic Environments: Deciding What To Monitor, Zohreh A. Dannenhauer Jan 2019

Anticipation In Dynamic Environments: Deciding What To Monitor, Zohreh A. Dannenhauer

Browse all Theses and Dissertations

In dynamic environments, external changes may occur that may affect planning decisions and goal choices. We claim that an intelligent agent should actively watch for what can go wrong and anticipate changes in the environment that allows the changing of its plan or changing of a given goal. In this thesis, we focus on the relationship between perception, act, interpretation, and planning. We claim that these components are not independent and need to interact with each other to help the agent succeed in achieving its goals and plans. If newly encountered world information affects the plan, the agent adapts to ...


Software Implementations And Applications Of Elliptic Curve Cryptography, Kirill Kultinov Jan 2019

Software Implementations And Applications Of Elliptic Curve Cryptography, Kirill Kultinov

Browse all Theses and Dissertations

Elliptic Curve Cryptography (ECC) is a public-key cryptography system. Elliptic Curve Cryptography (ECC) can achieve the same level of security as the public-key cryptography system, RSA, with a much smaller key size. It is a promising public key cryptography system with regard to time efficiency and resource utilization. This thesis focuses on the software implementations of ECC over finite field GF(p) with two distinct implementations of the Big Integer classes using character arrays, and bit sets in C++ programming language. Our implementation works on the ECC curves of the form y^2 = x^3 + ax + b (mod p). The ...


Use Of Virtual Reality Technology In Medical Training And Patient Rehabilitation, Sankalp Mishra Jan 2019

Use Of Virtual Reality Technology In Medical Training And Patient Rehabilitation, Sankalp Mishra

Browse all Theses and Dissertations

Coaching patients to follow the rehabilitation routines correctly and timely after surgery is often a challenge due to the limited medical knowledge of patients and limited availability of clinicians. Similarly, it is also a challenge to train medical professionals with both the technical and communication skills required in their practices. The recent emergence of VR technologies shines the light on improving the current training practices. In this thesis research, I will look at the development and application of VR-based immersive training games for two particular cases: 1. Post hand surgery rehab; and, 2. Training for Social determinants of health (SDOH ...


Automated Vehicle Electronic Control Unit (Ecu) Sensor Location Using Feature-Vector Based Comparisons, Gregory S. Buthker Jan 2019

Automated Vehicle Electronic Control Unit (Ecu) Sensor Location Using Feature-Vector Based Comparisons, Gregory S. Buthker

Browse all Theses and Dissertations

In the growing world of cybersecurity, being able to map and analyze how software and hardware interact is key to understanding and protecting critical embedded systems like the Engine Control Unit (ECU). The aim of our research is to use our understanding of the ECU's control flow attained through manual analysis to automatically map and identify sensor functions found within the ECU. We seek to do this by generating unique sets of feature vectors for every function within the binary file of a car ECU, and then using those feature sets to locate functions within each binary similar to ...


Scalable Clustering For Immune Repertoire Sequence Analysis, Prem Bhusal Jan 2019

Scalable Clustering For Immune Repertoire Sequence Analysis, Prem Bhusal

Browse all Theses and Dissertations

The development of the next-generation sequencing technology has enabled systems immunology researchers to conduct detailed immune repertoire analysis at the molecule level. Large sequence datasets (e.g., millions of sequences) are being collected to comprehensively understand how the immune system of a patient evolves over different stages of disease development. A recent study has shown that the hierarchical clustering (HC) algorithm gives the best results for B-cell clones analysis - an important type of immune repertoire sequencing (IR-Seq) analysis. However, due to the inherent complexity, the classical hierarchical clustering algorithm does not scale well to large sequence datasets. Surprisingly, no algorithms ...


Recognition Of Incomplete Objects Based On Synthesis Of Views Using A Geometric Based Local-Global Graphs, Michael Christopher Robbeloth Jan 2019

Recognition Of Incomplete Objects Based On Synthesis Of Views Using A Geometric Based Local-Global Graphs, Michael Christopher Robbeloth

Browse all Theses and Dissertations

The recognition of single objects is an old research field with many techniques and robust results. The probabilistic recognition of incomplete objects, however, remains an active field with challenging issues associated to shadows, illumination and other visual characteristics. With object incompleteness, we mean missing parts of a known object and not low-resolution images of that object. The employment of various single machine-learning methodologies for accurate classification of the incomplete objects did not provide a robust answer to the challenging problem. In this dissertation, we present a suite of high-level, model-based computer vision techniques encompassing both geometric and machine learning approaches ...


Accelerating Reverse Engineering Image Processing Using Fpga, Matthew Joshua Harris Jan 2019

Accelerating Reverse Engineering Image Processing Using Fpga, Matthew Joshua Harris

Browse all Theses and Dissertations

In recent decades, field programmable gate arrays (FPGAs) have evolved beyond simple, expensive computational components with minimal computing power to complex, inexpensive computational engines. Today, FPGAs can perform algorithmically complex problems with improved performance compared to sequential CPUs by taking advantage of parallelization. This concept can be readily applied to the computationally dense field of image manipulation and analysis. Processed on a standard CPU, image manipulation suffers with large image sets processed by highly sequential algorithms, but by carefully adhering to data dependencies, parallelized FPGA functions or kernels offer the possibility of significant improvement through threaded CPU functions. This thesis ...


Leveraging Schema Information For Improved Knowledge Graph Navigation, Rama Someswar Chittella Jan 2019

Leveraging Schema Information For Improved Knowledge Graph Navigation, Rama Someswar Chittella

Browse all Theses and Dissertations

Over the years, the semantic web has emerged as a new generation of the world wide web featuring advanced technologies and research contributions. It has revolutionized the usage of information by allowing users to capture and publish machine-understandable data and expedite methods such as ontologies to perform the same. These ontologies help in the formal representation of a specified domain and foster comprehensive machine understanding. Although, the engineering of ontologies and usage of logic have been an integral part of the web semantics, new areas of research such as the semantic web search, linking and usage of open data on ...


Conditional Dilated Attention Tracking Model - C-Datm, Tyler Clayton Highlander Jan 2019

Conditional Dilated Attention Tracking Model - C-Datm, Tyler Clayton Highlander

Browse all Theses and Dissertations

Current commercial tracking systems do not process images fast enough to perform target-tracking in real- time. State-of-the-art methods use entire scenes to locate objects frame-by-frame and are commonly computationally expensive because they use image convolutions. Alternatively, attention mechanisms track more efficiently by mimicking human optical cognitive interaction to only process small portions of an image. Thus, in this work we use an attention-based approach to create a model called C-DATM (Conditional Dilated Attention tracking Model) that learns to compare target features in a sequence of image-frames using dilated convolutions. The C-DATM is tested using the Modified National Institute of Standards ...


Static Evaluation Of Type Inference And Propagation On Global Variables With Varying Context, Ivan Frasure Jan 2019

Static Evaluation Of Type Inference And Propagation On Global Variables With Varying Context, Ivan Frasure

Browse all Theses and Dissertations

Software reverse engineering (SRE) is a broad field with motivations ranging from verifying or documenting gordian source code files to understanding and reimplementing binary object files and executables. SRE of binaries is exceptionally compelling and challenging due to large amounts of information that can be lost in the compilation progress. A central area in SRE is type inference. Type inference is built around a fundamental step in understanding the behavior of a binary, recovering the types of data in the program. Type inference has many unique techniques in both static and dynamic type inference systems that have been implemented in ...


Rules With Right Hand Existential Or Disjunction With Rowltab, Sri Jitendra Satpathy Jan 2019

Rules With Right Hand Existential Or Disjunction With Rowltab, Sri Jitendra Satpathy

Browse all Theses and Dissertations

One hotly debated research topic is, “What is the best approach for modeling ontologies?”. In the earlier stages of modeling ontologies, researchers have favored the usage of description logic to capture knowledge. One such choice is the Web Ontology Language (OWL) that is based on description logic. Many tools were designed around this principle and are still widely being used to model and explore ontologies. However, not all users find description logic to be intuitive, at least not without an extensive background in formal logics. Due to this, researchers have tried to explore other ways that will enable such users ...


Abusive And Hate Speech Tweets Detection With Text Generation, Abhishek Nalamothu Jan 2019

Abusive And Hate Speech Tweets Detection With Text Generation, Abhishek Nalamothu

Browse all Theses and Dissertations

According to a Pew Research study, 41% of Americans have personally experienced online harassment and two-thirds of Americans have witnessed harassment in 2017. Hence, online harassment detection is vital for securing and sustaining the popularity and viability of online social networks. Machine learning techniques play a crucial role in automatic harassment detection. One of the challenges of using supervised approaches is training data imbalance. Existing text generation techniques can help augment the training data, but they are still inadequate and ineffective. This research explores the role of domain-specific knowledge to complement the limited training data available for training a text ...


A Framework To Understand Emoji Meaning: Similarity And Sense Disambiguation Of Emoji Using Emojinet, Sanjaya Wijeratne Jan 2018

A Framework To Understand Emoji Meaning: Similarity And Sense Disambiguation Of Emoji Using Emojinet, Sanjaya Wijeratne

Browse all Theses and Dissertations

Pictographs, commonly referred to as `emoji’, have become a popular way to enhance electronic communications. They are an important component of the language used in social media. With their introduction in the late 1990’s, emoji have been widely used to enhance the sentiment, emotion, and sarcasm expressed in social media messages. They are equally popular across many social media sites including Facebook, Instagram, and Twitter. In 2015, Instagram reported that nearly half of the photo comments posted on Instagram contain emoji, and in the same year, Twitter reported that the `face with tears of joy’ emoji has been tweeted ...


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

Slim Embedding Layers For Recurrent Neural Language Models, Zhongliang Li

Browse all Theses and Dissertations

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 Jan 2018

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

Browse all Theses and Dissertations

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

Browse all Theses and Dissertations

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

Browse all Theses and Dissertations

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

Browse all Theses and Dissertations

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 ...


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

Browse all Theses and Dissertations

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

Browse all Theses and Dissertations

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 ...


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

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

Browse all Theses and Dissertations

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 ...


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

Malware Analysis Skills Taught In University Courses, Swetha Gorugantu

Browse all Theses and Dissertations

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 ...


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

Browse all Theses and Dissertations

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 ...