Computer Engineering Commons^™

Formal Language Constraints In Deep Reinforcement Learning For Self-Driving Vehicles, Tyler Bienhoff

School of Computing: Dissertations, Theses, and Student Research

In recent years, self-driving vehicles have become a holy grail technology that, once fully developed, could radically change the daily behaviors of people and enhance safety. The complexities of controlling a car in a constantly changing environment are too immense to directly program how the vehicle should behave in each specific scenario. Thus, a common technique when developing autonomous vehicles is to use reinforcement learning, where vehicles can be trained in simulated and real-world environments to make proper decisions in a wide variety of scenarios. Reinforcement learning models, however, have uncertainties in how the vehicle acts, especially in a previously …

Vector Magneto-Optical Generalized Ellipsometry On Magnetic Slanted Columnar Heterostructured Thin Films, Chad Briley

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

Modern material growth techniques allow for nano-engineering highly complex three dimensionally nanostructured materials. These nano-engineered materials possess highly anisotropic physical properties that are significantly different from that of their bulk counterparts. The magnetization properties of nano-engineered materials can be modified through a close range interaction known as magnetic exchange. These materials are referred to as magnetic exchange-coupled materials. Exchange-coupled magnetic materials are composite magnetic materials where the magnetization of one material is influenced by the magnetization state of the neighboring materials.

The author describes the creation of a representative sample set of exchange-coupled nanoengineered magnetic materials. These materials are created …

Power-Over-Tether Uas Leveraged For Nearly-Indefinite Meteorological Data Acquisition, Daniel Rico, Carrick Detweiler, Francisco Muñoz-Arriola

School of Computing: Dissertations, Theses, and Student Research

Use of unmanned aerial systems (UASs) in agriculture has risen in the past decade. These systems are key to modernizing agriculture. UASs collect and elucidate data previously difficult to obtain and used to help increase agricultural efficiency and production. Typical commercial off-the-shelf (COTS) UASs are limited by small payloads and short flight times. Such limits inhibit their ability to provide abundant data at multiple spatiotemporal scales. In this paper, we describe the design and construction of the tethered aircraft unmanned system (TAUS), which is a novel power-over-tether UAS leveraging the physical presence of the tether to launch multiple sensors along …

Learning Acoustic Word Embeddings With Dynamic Time Warping Triplet Networks, Denis Shitov, Elena Pirogova, Tadeusz A. Wysocki, Margaret Lech

Department of Electrical and Computer Engineering: Faculty Publications

In the last years, acoustic word embeddings (AWEs) have gained significant interest in the research community. It applies specifically to the application of acoustic embeddings in the Query-by Example Spoken Term Detection (QbE-STD) search and related word discrimination tasks. It has been shown that AWEs learned for the word or phone classification in one or several languages can outperform approaches that use dynamic time warping (DTW). In this paper, a new method of learning AWEs in the DTW framework is proposed. It employs a multitask triplet neural network to generate the AWEs. The triplet network learns acoustic representations of words …

The Effects Of Computer And Information Technology On Education, Iwasan D. Kejawa

School of Computing: Faculty Publications

In the society of ours, is it true really that computers and information technology have contributed immensely to the way we learn? After observing and reading various educational paraphernalia and scanning the environment research has shown that the educational systems have greatly been impacted by computers and information technology. With the growth of technology, the ways we learn have been improved tremendously. Innovative technologies have contributed to the innovation of learning in the education arena and outside. The traditional ways of conveying instructions to learners have been augmented with the use of computers information technologies. The educational system of our …

Reducing Run-Time Adaptation Space Via Analysis Of Possible Utility Bounds, Clay Stevens, Hamid Bagheri

School of Computing: Conference and Workshop Papers

Self-adaptive systems often employ dynamic programming or similar techniques to select optimal adaptations at run-time. These techniques suffer from the “curse of dimensionality", increasing the cost of run-time adaptation decisions. We propose a novel approach that improves upon the state-of-the-art proactive self-adaptation techniques to reduce the number of possible adaptations that need be considered for each run-time adaptation decision. The approach, realized in a tool called Thallium, employs a combination of automated formal modeling techniques to (i) analyze a structural model of the system showing which configurations are reachable from other configurations and (ii) compute the utility that can be …

A Quantile-Based Approach For Transmission Expansion Planning, Jairo Cervantes, F. Fred Choobineh

Department of Electrical and Computer Engineering: Faculty Publications

Transmission expansion planning is an integral part of power system planning and consists of generating and selecting transmission proposals for maintaining sufficient transmission capacity to satisfy the electric load. Specifically, the desire to increase the use of renewable energy has exposed the limitations of transmission networks and has elevated the importance of transmission expansion planning. However, considering the random nature of renewable sources in conjunction with the power outages makes the planning process very challenging. We present a new procedure for selecting the best transmission enhancement proposal from a set of finite proposals under uncertainty. The selection is based on …

Joint-Srvdnet: Joint Super Resolution And Vehicle Detection Network, Moktari Mostofa, Syeda Nyma Ferdous, Benjamin S. Riggan, Nasser M. Nasrabadi

Department of Electrical and Computer Engineering: Faculty Publications

In many domestic and military applications, aerial vehicle detection and super-resolution algorithms are frequently developed and applied independently. However, aerial vehicle detection on super resolved images remains a challenging task due to the lack of discriminative information in the super-resolved images. To address this problem, we propose a Joint Super-Resolution and Vehicle Detection Network (Joint SRVDNet) that tries to generate discriminative, high-resolution images of vehicles from low-resolution aerial images. First, aerial images are up-scaled by a factor of 4x using a Multi-scale Generative Adversarial Network (MsGAN), which has multiple intermediate outputs with increasing resolutions. Second, a detector is trained on …

Stochastic Simulation Of Cellular Metabolism, Emalie J. Clement, Thomas T. Schulze, Ghada A. Soliman, Beata Joanna Wysocki, Paul H. Davis, Tadeusz A. Wysocki

Department of Electrical and Computer Engineering: Faculty Publications

Increased technological methods have enabled the investigation of biology at nanoscale levels. Such systems require the use of computational methods to comprehend the complex interactions that occur. The dynamics of metabolic systems have been traditionally described utilizing differential equations without fully capturing the heterogeneity of biological systems. Stochastic modeling approaches have recently emerged with the capacity to incorporate the statistical properties of such systems. However, the processing of stochastic algorithms is a computationally intensive task with intrinsic limitations. Alternatively, the queueing theory approach, historically used in the evaluation of telecommunication networks, can significantly reduce the computational power required to generate …

Understanding Eye Gaze Patterns In Code Comprehension, Jonathan Saddler

School of Computing: Dissertations, Theses, and Student Research

Program comprehension is a sub-field of software engineering that seeks to understand how developers understand programs. Comprehension acts as a starting point for many software engineering tasks such as bug fixing, refactoring, and feature creation. The dissertation presents a series of empirical studies to understand how developers comprehend software in realistic settings. The unique aspect of this work is the use of eye tracking equipment to gather fine-grained detailed information of what developers look at in software artifacts while they perform realistic tasks in an environment familiar to them, namely a context including both the Integrated Development Environment (Eclipse or …

Small Mode Volume Plasmonic Film-Coupled Nanostar Resonators, Negar Charchi, Ying Li, Margaret Huber, Elyahb Allie Kwizera, Xiaohua Huang, Christos Argyropoulos, Thang Hoang

Department of Electrical and Computer Engineering: Faculty Publications

Confining and controlling light in extreme subwavelength scales are tantalizing tasks. In this work, we report a study of individual plasmonic film-coupled nanostar resonators where polarized plasmonic optical modes are trapped in ultrasmall volumes. Individual gold nanostars, separated from a flat gold film by a thin dielectric spacer layer, exhibit a strong light confinement between the sub-10 nm volume of the nanostar's tips and the film. Through dark field scattering measurements of many individual nanostars, a statistical observation of the scattered spectra is obtained and compared with extensive simulation data to reveal the origins of the resonant peaks. We observe …

Deep Learning And Polar Transformation To Achieve A Novel Adaptive Automatic Modulation Classification Framework, Pejman Ghasemzadeh

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

Automatic modulation classification (AMC) is an approach that can be leveraged to identify an observed signal's most likely employed modulation scheme without any a priori knowledge of the intercepted signal. Of the three primary approaches proposed in literature, which are likelihood-based, distribution test-based, and feature-based (FB), the latter is considered to be the most promising approach for real-world implementations due to its favorable computational complexity and classification accuracy. FB AMC is comprised of two stages: feature extraction and labeling. In this thesis, we enhance the FB approach in both stages. In the feature extraction stage, we propose a new architecture …

Emotional Awareness During Bug Fixes: A Pilot Study, Jada O. Loro, Abigail L. Schneff, Sarah J. Oran, Bonita Sharif

School of Computing: Dissertations, Theses, and Student Research

This study examines the effects of a programmer's emotional awareness on progress while fixing bugs. The goal of the study is to capitalize on emotional awareness to ultimately increase progress made during software development. This process could result in improved software maintenance.

An Eye Tracking Replication Study Of A Randomized Controlled Trial On The Effects Of Embedded Computer Language Switching, Cole Peterson

School of Computing: Dissertations, Theses, and Student Research

The use of multiple programming languages (polyglot programming) during software development is common practice in modern software development. However, not much is known about how the use of these different languages affects developer productivity. The study presented in this thesis replicates a randomized controlled trial that investigates the use of multiple languages in the context of database programming tasks. Participants in our study were given coding tasks written in Java and one of three SQL-like embedded languages: plain SQL in strings, Java methods only, a hybrid embedded language that was more similar to Java. In addition to recording the online …

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

School of Computing: 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.

Advisor: Peter Z. Revesz

A Memory Usage Comparison Between Jitana And Soot, Yuanjiu Hu

School of Computing: 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 …

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

School of Computing: 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 …

Advanced Techniques To Detect Complex Android Malware, Zhiqiang Li

School of Computing: 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 …

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

School of Computing: 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 …

Low Latency Bearing Fault Detection Of Direct-Drive Wind Turbines Using Stator Current, Samrat Nath, Jingxian Wu, Yue Zhao, Wei Qiao

Department of Electrical and Computer Engineering: Faculty Publications

Low latency change detection aims to minimize the detection delay of an abrupt change in probability distributions of a random process, subject to certain performance constraints such as the probability of false alarm (PFA). In this paper, we study the low latency detection of bearing faults of direct-drive wind turbines (WT), by analyzing the statistical behaviors of stator currents generated by the WT in real-time. It is discovered that the presence of fault will affect the statistical distribution of WT stator current amplitude at certain frequencies. Since the signature of a fault can appear in one of the multiple possible …

Innovation In Pedagogy And Technology Symposium, 2019: Selected Conference Proceedings, University Of Nebraska Online, University Of Nebraska Information Technology Services

Zea E-Books Collection

Advancing Technology in Education at the University of Nebraska, May 7, 2019

Welcome Address • Susan Fritz, Ph.D., Executive Vice President and Provost, University of Nebraska 6

Opening Remarks • Mary Niemiec, Associate Vice President for Digital Education, Director of University of Nebraska Online 6

Keynote Presentation: Shaping the Next Generation of Higher Education • Bryan Alexander, Ph.D. 6

Featured Extended Presentation: Redesigning Courses & Determining Effectiveness Through Research • Tanya Joosten, University of Wisconsin-Milwaukee (UWM), Erin Blankenship, Ph.D. (UNL), Ella Burnham (UNL), Nate Eidem, Ph.D. (UNK), Marnie Imhoff (UNMC), Linsey Donner (UNMC), Ellie Miller (UNMC) 7

5 Ways to …

Scalable Universal Space Vector Pulse Width Modulation Scheme For Multilevel Inverters, Wei Qiao, Fa Chen, Liyan Qu

Department of Electrical and Computer Engineering: Faculty Publications

A scalable universal space vector pulse-width modulation (SVPWM) scheme for multilevel inverters is disclosed. In the disclosed SVPWM scheme, the modulation triable is quickly identified based on a coordinate transformation from an α-β coordinate system to a 120^o oblique coordinate system. Then, the duty cycles and switching states of the three vertices of the modulation triangle are determined by simple algebraic computations. In a switching period, any vertex of the modulation triangle can be flexibly selected as the start point to optimize the switching sequence with flexibly adjustable duty cycle(s) for the redundant switching state(s) according to specific applications.

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

University of Nebraska-Lincoln Libraries: Presentations

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.

Comparative Analysis Of Single-Cell Transcriptomics In Human And Zebrafish Oocytes, Handan Can, Sree K. Chanumolu, Elena Gonzalez-Muñoz, Sukumal Prukudom, Hasan H. Otu, Jose Cibelli

Department of Electrical and Computer Engineering: Faculty Publications

Background: Zebrafish is a popular model organism, which is widely used in developmental biology research. Despite its general use, the direct comparison of the zebrafish and human oocyte transcriptomes has not been well studied. It is significant to see if the similarity observed between the two organisms at the gene sequence level is also observed at the expression level in key cell types such as the oocyte.

Results: We performed single-cell RNA-seq of the zebrafish oocyte and compared it with two studies that have performed single-cell RNA-seq of the human oocyte. We carried out a comparative analysis of genes expressed …

Cdc42-Dependent Transfer Of Mir301 From Breast Cancer-Derived Extracellular Vesicles Regulates The Matrix Modulating Ability Of Astrocytes At The Blood–Brain Barrier, Golnaz Morad, Cassandra C. Daisy, Hasan H. Otu, Towia A. Libermann, Simon T. Dillon, Marsha A. Moses

Department of Electrical and Computer Engineering: Faculty Publications

Breast cancer brain metastasis is a major clinical challenge and is associated with a dismal prognosis. Understanding the mechanisms underlying the early stages of brain metastasis can provide opportunities to develop efficient diagnostics and therapeutics for this significant clinical challenge. We have previously reported that breast cancer-derived extracellular vesicles (EVs) breach the blood–brain barrier (BBB) via transcytosis and can promote brain metastasis. Here, we elucidate the functional consequences of EV transport across the BBB. We demonstrate that brain metastasis-promoting EVs can be internalized by astrocytes and modulate the behavior of these cells to promote extracellular matrix remodeling in vivo. We …

Ieee Access Special Section Editorial: Green Signal Processing For Wireless Communicationsand Networking, Wen-Long Chin, David Shiung, Yi Qian, Woongsup Lee, Andres Kwasinki, Yansha Deng

Department of Electrical and Computer Engineering: Faculty Publications

No abstract provided.

Cdc42-Dependent Transfer Of Mir301 From Breast Cancer-Derived Extracellular Vesicles Regulates The Matrix Modulating Ability Of Astrocytes At The Blood–Brain Barrier, Golnaz Morad, Cassandra C. Daisy, Hasan H. Otu, Towia A. Libermann, Simon T. Dillon, Marsha A. Moses

Department of Electrical and Computer Engineering: Faculty Publications

Breast cancer brain metastasis is a major clinical challenge and is associated with a dismal prognosis. Understanding the mechanisms underlying the early stages of brain metastasis can provide opportunities to develop efficient diagnostics and therapeutics for this significant clinical challenge. We have previously reported that breast cancer-derived extracellular vesicles (EVs) breach the blood–brain barrier (BBB) via transcytosis and can promote brain metastasis. Here, we elucidate the functional consequences of EV transport across the BBB. We demonstrate that brain metastasis-promoting EVs can be internalized by astrocytes and modulate the behavior of these cells to promote extracellular matrix remodeling in vivo. We …

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

School of Computing: 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

School of Computing: 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 …

Impact Of Direction Parameter In Performance Of Modified Aodv In Vanet, Afsana Ahamed, Hamid Vakilzadian

Department of Electrical and Computer Engineering: Faculty Publications

A vehicular ad hoc network (VANET) is a technology in which moving cars are used as routers (nodes) to establish a reliable mobile communication network among the vehicles. Some of the drawbacks of the routing protocol, Ad hoc On-Demand Distance Vector (AODV), associated with VANETs are the end-to-end delay and packet loss. We modified the AODV routing protocols to reduce the number of route request (RREQ) and route reply (RREP) messages by adding direction parameters and two-step filtering. The two-step filtering process reduces the number of RREQ and RREP packets, reduces the packet overhead, and helps to select the stable …