Computer Engineering Commons^™

A Memory Usage Comparison Between Jitana And Soot, Yuanjiu Hu

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

There are several factors that make analyzing Android apps to address dependability and security concerns challenging. These factors include (i) resource efficiency as analysts need to be able to analyze large code-bases to look for issues that can exist in the application code and underlying platform code; (ii) scalability as today’s cybercriminals deploy attacks that may involve many participating apps; and (iii) in many cases, security analysts often rely on dynamic or hybrid analysis techniques to detect and identify the sources of issues.

The underlying principle governing the design of existing program analysis engines is the main cause that prevents …

An Algorithm For Building Language Superfamilies Using Swadesh Lists, Bill Mutabazi

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The main contributions of this thesis are the following: i. Developing an algorithm to generate language families and superfamilies given for each input language a Swadesh list represented using the international phonetic alphabet (IPA) notation. ii. The algorithm is novel in using the Levenshtein distance metric on the IPA representation and in the way it measures overall distance between pairs of Swadesh lists. iii. Building a Swadesh list for the author's native Kinyarwanda language because a Swadesh list could not be found even after an extensive search for it.

Adviser: Peter Revesz

Advanced Techniques To Detect Complex Android Malware, Zhiqiang Li

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Android is currently the most popular operating system for mobile devices in the world. However, its openness is the main reason for the majority of malware to be targeting Android devices. Various approaches have been developed to detect malware.

Unfortunately, new breeds of malware utilize sophisticated techniques to defeat malware detectors. For example, to defeat signature-based detectors, malware authors change the malware’s signatures to avoid detection. As such, a more effective approach to detect malware is by leveraging malware’s behavioral characteristics. However, if a behavior-based detector is based on static analysis, its reported results may contain a large number of …

Open Dynamic Interaction Network: A Cell-Phone Based Platform For Responsive Ema, Gisela Font Sayeras

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The study of social networks is central to advancing our understanding of a wide range of phenomena in human societies. Social networks co-evolve concurrently alongside the individuals within them. Selection processes cause network structure to change in response to emerging similarities/differences between individuals. At the same time, diffusion processes occur as individuals influence one another when they interact across network links. Indeed, each network link is a logical abstraction that aggregates many short-lived pairwise interactions of interest that are being studied. Traditionally, network co-evolution is studied by periodically taking static snapshots of social networks using surveys. Unfortunately, participation incentives …

An Anns Based Failure Detection Method For Onos Sdon Controller, Shideh Yavary Mehr

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Network reachability is an important factor of an optical telecommunication network. In a wavelength-division-muliplexing (WDM) optical network, any failure can cause a large amount of loss and disruptions in network. Failures can occur in network elements, link, and component inside a node or etc. Since major network disruptions can caused network performance degradations, it is necessary that operators have solutions to prevent such those failures. This work examines a prediction model in optical networks and propose a protection plan using a Machine Learning (ML) algorithm called Artificial Neural Networks (ANN) using Mininet emulator. ANN is one of the best method …

Algorithms Of Oppression [Uno Pa Theory Proseminar Presentation], Sue Ann Gardner

University of Nebraska-Lincoln Libraries: Conference Presentations and Speeches

Slides of two classes taught in the Theory Proseminar in the School of Public Administration at the University of Nebraska at Omaha by Sue Ann Gardner on February 11 and 18, 2020.

Connects information theory to applicable knowledge frameworks in public administration. Includes an in-depth discussion of the concepts addressed in Samiya Umoja Noble's book Algorithms of Oppression (published by New York University Press, New York, New York, United States, 2018) in the context of public administration and public academic libraries.

Power-Over-Tether Uas Leveraged For Nearly Indefinite Meteorological Data Acquisition In The Platte River Basin, Daniel Rico, Carrick Detweiler, Francisco Munoz-Arriola

CSE Conference and Workshop Papers

The integration of unmanned aerial systems (UASs) has increased in the field of agriculture. These systems can provide data that was previously difficult to obtain to help increase efficiency and production. Typical commercial off the shelf (COTS) UASs have significant limitations in the form of small payloads, and short flight times which inhibit their ability to provide significant quantities of useful data. We present the development of a novel power-over-tether UAS that leverages the physical presence of the tether to integrate sensors at multiple altitudes along the tether. The UAS can acquire data nearly indefinitely to sense atmospheric conditions and …

Designing Shared Control Strategies For Teleoperated Robots Across Intrinsic User Qualities, Nancy Pham

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Accounting for variance in human behavior is an integral part of interacting with robotic systems that share control between users and robots in order to reduce errors, improve performance, and maintain safety. In this work we focus on the shared control of a telepresence robot and how individual user traits may affect a person's performance while navigating the robot. This requires understanding which user qualities impact performance and cause conflicts -- with the ultimate goal of building shared controllers that adapt to those qualities. Toward this goal, we develop novel adaptive shared controllers and integrate the study of intrinsic user …

Comparison Of Object Detection And Patch-Based Classification Deep Learning Models On Mid- To Late-Season Weed Detection In Uav Imagery, Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li, Stephen Scott, Eric T. Psota, Amit J. Jhala, Joe D. Luck, Yeyin Shi

Department of Biological Systems Engineering: Papers and Publications

Mid- to late-season weeds that escape from the routine early-season weed management threaten agricultural production by creating a large number of seeds for several future growing seasons. Rapid and accurate detection of weed patches in field is the first step of site-specific weed management. In this study, object detection-based convolutional neural network models were trained and evaluated over low-altitude unmanned aerial vehicle (UAV) imagery for mid- to late-season weed detection in soybean fields. The performance of two object detection models, Faster RCNN and the Single Shot Detector (SSD), were evaluated and compared in terms of weed detection performance using mean …

Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Emergent software ecosystems, boomed by the advent of smartphones and the Internet of Things (IoT) platforms, are perpetually sophisticated, deployed into highly dynamic environments, and facilitating interactions across heterogeneous domains. Accordingly, assessing the security thereof is a pressing need, yet requires high levels of scalability and reliability to handle the dynamism involved in such volatile ecosystems.

This dissertation seeks to enhance conventional security detection methods to cope with the emergent features of contemporary software ecosystems. In particular, it analyzes the security of Android and IoT ecosystems by developing rigorous vulnerability detection methods. A critical aspect of this work is the …

Domain Adaptation In Unmanned Aerial Vehicles Landing Using Reinforcement Learning, Pedro Lucas Franca Albuquerque

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Landing an unmanned aerial vehicle (UAV) on a moving platform is a challenging task that often requires exact models of the UAV dynamics, platform characteristics, and environmental conditions. In this thesis, we present and investigate three different machine learning approaches with varying levels of domain knowledge: dynamics randomization, universal policy with system identification, and reinforcement learning with no parameter variation. We first train the policies in simulation, then perform experiments both in simulation, making variations of the system dynamics with wind and friction coefficient, then perform experiments in a real robot system with wind variation. We initially expected that providing …

Formal Modeling And Analysis Of A Family Of Surgical Robots, Niloofar Mansoor

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Safety-critical applications often use dependability cases to validate that specified properties are invariant, or to demonstrate a counterexample showing how that property might be violated. However, most dependability cases are written with a single product in mind. At the same time, software product lines (families of related software products) have been studied with the goal of modeling variability and commonality and building family-based techniques for both modeling and analysis. This thesis presents a novel approach for building an end to end dependability case for a software product line, where a property is formally modeled, a counterexample is found and then …

Image Classification Using Fuzzy Fca, Niruktha Roy Gotoor

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Formal concept analysis (FCA) is a mathematical theory based on lattice and order theory used for data analysis and knowledge representation. It has been used in various domains such as data mining, machine learning, semantic web, Sciences, for the purpose of data analysis and Ontology over the last few decades. Various extensions of FCA are being researched to expand it's scope over more departments. In this thesis,we review the theory of Formal Concept Analysis (FCA) and its extension Fuzzy FCA. Many studies to use FCA in data mining and text learning have been pursued. We extend these studies to include …

A Co-Optimal Coverage Path Planning Method For Aerial Scanning Of Complex Structures, Zhexiong Shang, Justin Bradley, Zhigang Shen

Department of Construction Engineering and Management: Faculty Publications

The utilization of unmanned aerial vehicles (UAVs) in survey and inspection of civil infrastructure has been growing rapidly. However, computationally efficient solvers that find optimal flight paths while ensuring high-quality data acquisition of the complete 3D structure remains a difficult problem. Existing solvers typically prioritize efficient flight paths, or coverage, or reducing computational complexity of the algorithm – but these objectives are not co-optimized holistically. In this work we introduce a co-optimal coverage path planning (CCPP) method that simultaneously co-optimizes the UAV path, the quality of the captured images, and reducing computational complexity of the solver all while adhering to …

Global Research Trend On Cyber Security: A Scientometric Analysis, Somesh Rai, Kunwar Singh Dr, Akhilesh Kumar Varma

Library Philosophy and Practice (e-journal)

Scientometrics is a quantitative analysis of scholarly literature related to a particular subject or area (well defined by some limits, scope and coverage), which helps to understand different aspects about the scholarly literature’s growth in various dimensions of knowledge. Similarly, this study is a quantitative analysis of the Global research trends in cyber security. Some works related to scientometrics of ‘deception, counter-deception in cyberspace’ had been published in 2011, but we have focused on ‘cyber security’ as the topic of research. For analysis we have utilised the published data available in Scopus database, which is directly related to ‘cyber security’. …

Learnfca: A Fuzzy Fca And Probability Based Approach For Learning And Classification, Suraj Ketan Samal

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Formal concept analysis(FCA) is a mathematical theory based on lattice and order theory used for data analysis and knowledge representation. Over the past several years, many of its extensions have been proposed and applied in several domains including data mining, machine learning, knowledge management, semantic web, software development, chemistry ,biology, medicine, data analytics, biology and ontology engineering.

This thesis reviews the state-of-the-art of theory of Formal Concept Analysis(FCA) and its various extensions that have been developed and well-studied in the past several years. We discuss their historical roots, reproduce the original definitions and derivations with illustrative examples. Further, we provide …

Exploring Eye Tracking Data On Source Code Via Dual Space Analysis, Li Zhang

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Eye tracking is a frequently used technique to collect data capturing users' strategies and behaviors in processing information. Understanding how programmers navigate through a large number of classes and methods to find bugs is important to educators and practitioners in software engineering. However, the eye tracking data collected on realistic codebases is massive compared to traditional eye tracking data on one static page. The same content may appear in different areas on the screen with users scrolling in an Integrated Development Environment (IDE). Hierarchically structured content and fluid method position compose the two major challenges for visualization. We present a …

Distributed Edge Bundling For Large Graphs, Yves Tuyishime

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Graphs or networks are widely used to depict the relationships between data entities in diverse scientific and engineering applications. A direct visualization (such as node-link diagram) of a graph with a large number of nodes and edges often incurs visual clutter. To address this issue, researchers have developed edge bundling algorithms that visually merge similar edges into curved bundles and can effectively reveal high-level edge patterns with reduced visual clutter. Although the existing edge bundling algorithms achieve appealing results, they are mostly designed for a single machine, and thereby the size of a graph they can handle is limited by …

Dimensional Analysis Of Robot Software Without Developer Annotations, John-Paul W. Ore

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Robot software risks the hazard of dimensional inconsistencies. These inconsistencies occur when a program incorrectly manipulates values representing real-world quantities. Incorrect manipulation has real-world consequences that range in severity from benign to catastrophic. Previous approaches detect dimensional inconsistencies in programs but require extra developer effort and technical complications. The extra effort involves developers creating type annotations for every variable representing a real-world quantity that has physical units, and the technical complications include toolchain burdens like specialized compilers or type libraries.

To overcome the limitations of previous approaches, this thesis presents novel methods to detect dimensional inconsistencies without developer annotations. We …

The Design And Implementation Of Aida: Ancient Inscription Database And Analytics System, M Parvez Rashid

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

AIDA, the Ancient Inscription Database and Analytic system can be used to translate and analyze ancient Minoan language. The AIDA system currently stores three types of ancient Minoan inscriptions: Linear A, Cretan Hieroglyph and Phaistos Disk inscriptions. In addition, AIDA provides candidate syllabic values and translations of Minoan words and inscriptions into English. The AIDA system allows the users to change these candidate phonetic assignments to the Linear A, Cretan Hieroglyph and Phaistos symbols. Hence the AIDA system provides for various scholars not only a convenient online resource to browse Minoan inscriptions but also provides an analysis tool to explore …

User Privacy Leakage In Location-Based Mobile Ad Services, Qicheng Lin

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The online advertising ecosystem leverages its massive data collection capability to learn the properties of users for targeted ad deliveries. Many Android app developers include ad libraries in their apps as a way of monetization. These ad libraries contain advertisements from the sell-side platforms, which collect an extensive set of sensitive information to provide more relevant advertisements for their customers. Existing efforts have investigated the increasingly pervasive private data collection of mobile ad networks over time. However, there lacks a measurement study to evaluate the scale of privacy leakage of ad networks across different geographical areas. In this work, we …

Scheduling And Prefetching In Hadoop With Block Access Pattern Awareness And Global Memory Sharing With Load Balancing Scheme, Sai Suman

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Although several scheduling and prefetching algorithms have been proposed to improve data locality in Hadoop, there has not been much research to increase cluster performance by targeting the issue of data locality while considering the 1) cluster memory, 2) data access patterns and 3) real-time scheduling issues together.

Firstly, considering the data access patterns is crucial because the computation might access some portion of the data in the cluster only once while the rest could be accessed multiple times. Blindly retaining data in memory might eventually lead to inefficient memory utilization.

Secondly, several studies found that the cluster memory goes …

A Data Driven Approach To Identify Journalistic 5ws From Text Documents, Venkata Krishna Mohan Sunkara

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Textual understanding is the process of automatically extracting accurate high-quality information from text. The amount of textual data available from different sources such as news, blogs and social media is growing exponentially. These data encode significant latent information which if extracted accurately can be valuable in a variety of applications such as medical report analyses, news understanding and societal studies. Natural language processing techniques are often employed to develop customized algorithms to extract such latent information from text.

Journalistic 5Ws refer to the basic information in news articles that describes an event and include where, when, who, what and why …

A Data-Driven Approach For Detecting Stress In Plants Using Hyperspectral Imagery, Suraj Gampa

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

A phenotype is an observable characteristic of an individual and is a function of its genotype and its growth environment. Individuals with different genotypes are impacted differently by exposure to the same environment. Therefore, phenotypes are often used to understand morphological and physiological changes in plants as a function of genotype and biotic and abiotic stress conditions. Phenotypes that measure the level of stress can help mitigate the adverse impacts on the growth cycle of the plant. Image-based plant phenotyping has the potential for early stress detection by means of computing responsive phenotypes in a non-intrusive manner. A large number …

Image Processing Algorithms For Elastin Lamellae Inside Cardiovascular Arteries, Mahmoud Habibnezhad

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Automated image processing methods are greatly needed to replace the tedious, manual histology analysis still performed by many physicians. This thesis focuses on pathological studies that express the essential role of elastin lamella in the resilience and elastic properties of the arterial blood vessels. Due to the stochastic nature of the shape and distribution of the elastin layers, their morphological features appear as the best candidates to develop a mathematical formulation for the resistance behavior of elastic tissues. However, even for trained physicians and their assistants, the current measurement procedures are highly error-prone and prolonged. This thesis successfully integrates such …

Gaindroid: General Automated Incompatibility Notifier For Android Applications, Bruno Vieira Resende E Silva

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

With the ever-increasing popularity of mobile devices over the last decade, mobile apps and the frameworks upon which they are built frequently change. This rapid evolution leads to a confusing jumble of devices and applications utilizing differing features even within the same framework. For Android apps and devices, representing over 80% of the market share, mismatches between the version of the Android operating system installed on a device and the version of the app installed, can lead to several run-time crashes, providing a poor user experience.

This thesis presents GAINDroid, an analysis approach, backed with a classloader based program analyzer, …

Feasibility And Security Analysis Of Wideband Ultrasonic Radio For Smart Home Applications, Qi Xia

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Smart home Internet-of-Things (IoT) accompanied by smart home apps has witnessed tremendous growth in the past few years. Yet, the security and privacy of the smart home IoT devices and apps have raised serious concerns, as they are getting increasingly complicated each day, expected to store and exchange extremely sensitive personal data, always on and connected, and commonly exposed to any users in a sensitive environment. Nowadays wireless smart home IoT devices rely on electromagnetic wave-based radio-frequency (RF) technology to establish fast and reliable quality network connections. However, RF has its limitations that can negatively affect the smart home user …

Big Data Investment And Knowledge Integration In Academic Libraries, Saher Manaseer, Afnan R. Alawneh, Dua Asoudi

Copyright, Fair Use, Scholarly Communication, etc.

Recently, big data investment has become important for organizations, especially with the fast growth of data following the huge expansion in the usage of social media applications, and websites. Many organizations depend on extracting and reaching the needed reports and statistics. As the investments on big data and its storage have become major challenges for organizations, many technologies and methods have been developed to tackle those challenges.

One of such technologies is Hadoop, a framework that is used to divide big data into packages and distribute those packages through nodes to be processed, consuming less cost than the traditional storage …

The Global Disinformation Order: 2019 Global Inventory Of Organised Social Media Manipulation, Samantha Bradshaw, Philip N. Howard

Copyright, Fair Use, Scholarly Communication, etc.

Executive Summary

Over the past three years, we have monitored the global organization of social media manipulation by governments and political parties. Our 2019 report analyses the trends of computational propaganda and the evolving tools, capacities, strategies, and resources.

1. Evidence of organized social media manipulation campaigns which have taken place in 70 countries, up from 48 countries in 2018 and 28 countries in 2017. In each country, there is at least one political party or government agency using social media to shape public attitudes domestically.

2.Social media has become co-opted by many authoritarian regimes. In 26 countries, computational propaganda …

Gmaim: An Analytical Pipeline For Microrna Splicing Profiling Using Generative Model, Kan Liu

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

MicroRNAs (miRNAs) are a class of short (~22 nt) single strand RNA molecules predominantly found in eukaryotes. Being involved in many major biological processes, miRNAs can regulate gene expression by targeting mRNAs to facilitate their degradation or translational inhibition. The imprecise splicing of miRNA splicing which introduces severe variability in terms of sequences of miRNA products and their corresponding downstream gene expression regulation. For example, to study biogenesis of miRNAs, usually, biologists can deplete a gene in the miRNA biogenesis pathway and study the change of miRNA sequences, which can cause impression of miRNAs. Although high-throughput sequencing technologies such as …