Computer Engineering Commons^™

From Digital Traces To Marketing Insights: Recovering Consumer Preferences For Digital Entertainment Services And Online Shopping, Ai Phuong Hoang

Dissertations and Theses Collection (Open Access)

IT innovations disrupt traditional business models and challenge conventional thinking. Thus, industry incumbents face fierce competition from start-ups with new business models and new ways of engaging customers. Digital entertainment goods and personalized services have become a lucrative market, which has undergone a transformation enabled by seamless Internet connections. Meanwhile, social networks and other online platforms have brought people and business even closer.

Development Of Scalable Simulator For Spiking Neural Network, Jae Sang Ha

McKelvey School of Engineering Graduate Student Theses & Dissertations

A neural network simulator for Spiking Neural Network (SNN) is a useful research tool to model brain functions with a computer. With this tool, different parameters can be explored easily compared to using a real brain. For several decades, researchers have developed many software packages and simulators to accelerate research in computational neuroscience. However, despite their advantages, different neural simulators possess different limitations, such as flexibility of choosing different neuron models and scalability of simulators for large numbers of neurons. This paper demonstrates an efficient and scalable spiking neural simulator that is based on growth transform neurons and runs on …

Real-Time Streaming Video And Image Processing On Inexpensive Hardware With Low Latency, Richard L. Gregg

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

The use of resource constrained inexpensive hardware places restrictions on the design of streaming video and image processing system performance. In order to achieve acceptable frame-per-second (fps) performance with low latency, it is important to understand the response time requirements that the system needs to meet. For humans to be able to process and react to an image there should not be more than a 100ms delay between the time a camera captures an image and subsequently displays that image to the user.

In order to accomplish this goal, several design considerations need to be taken into account that limit …

Analyzing Requirements And Traceability Information To Improve Bug Localization, Michael Rath, David Lo, Patrick Mader

Research Collection School Of Computing and Information Systems

Locating bugs in industry-size software systems is time consuming and challenging. An automated approach for assisting the process of tracing from bug descriptions to relevant source code benefits developers. A large body of previous work aims to address this problem and demonstrates considerable achievements. Most existing approaches focus on the key challenge of improving techniques based on textual similarity to identify relevant files. However, there exists a lexical gap between the natural language used to formulate bug reports and the formal source code and its comments. To bridge this gap, state-of-the-art approaches contain a component for analyzing bug history information …

Building A Smart Nation: Singapore’S Digital Journey, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

The journey towards smart city status is a strong global trend as governments around the world strive to harness technology to improve the quality of life for their citizens (United Nations, 2016). The widespread phenomenon of becoming “smart” is a key topic of discussion and research that continues to change as new digital technologies develop (Ishkineeva et al., 2015). The smart cities theme is important because it explores how governments, as providers of public goods, harness digital technologies to improve the lives of citizens around the world in the present and the future.

A Qualitative Research On Marketing And Sales In The Artificial Intelligence Age, Yin Yang, Keng Siau

Research Collection School Of Computing and Information Systems

The age of artificial intelligence is here! Artificial Intelligence, robotics, machine learning, and automation are impacting the field of marketing and sales in an unprecedented way. In this study, the qualitative research methodology will be used to better understand the revolution and evolution of marketing and sales field in the AI age. Multiple case studies will be performed in various marketing and sales units in different organizations. This research is of value to both academics and practitioners as it aims to provide a detailed analysis and documentation of the changes in marketing and sales functionalities and job markets as AI …

Breathing-Based Authentication On Resource-Constrained Iot Devices Using Recurrent Neural Networks, Jagmohan Chauhan, Suranga Seneviratne, Yining Hu, Archan Misra, Aruna Seneviratne, Youngki Lee

Research Collection School Of Computing and Information Systems

Recurrent neural networks (RNNs) have shown promising resultsin audio and speech-processing applications. The increasingpopularity of Internet of Things (IoT) devices makes a strongcase for implementing RNN-based inferences for applicationssuch as acoustics-based authentication and voice commandsfor smart homes. However, the feasibility and performance ofthese inferences on resource-constrained devices remain largelyunexplored. The authors compare traditional machine-learningmodels with deep-learning RNN models for an end-to-endauthentication system based on breathing acoustics.

Real-Time Object Detection And Tracking On Drones, Tu Le

Maseeh Summer Undergraduate Research Experience

Unmanned aerial vehicles, also known as drones, have been more and more widely used in recent decades because of their mobility. They appear in many applications such as farming, search and rescue, entertainment, military, and so on. Such high demands for drones lead to the need of developments in drone technologies. Next generations of commercial and military drones are expected to be aware of surrounding objects while flying autonomously in different terrains and conditions. One of the biggest challenges to drone automation is the ability to detect and track objects of interest in real-time. While there are many robust machine …

K-Means: A Revisit, Wan-Lei Zhao, Cheng-Hao Deng, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Due to its simplicity and versatility, k-means remains popular since it was proposed three decades ago. The performance of k-means has been enhanced from different perspectives over the years. Unfortunately, a good trade-off between quality and efficiency is hardly reached. In this paper, a novel k-means variant is presented. Different from most of k-means variants, the clustering procedure is driven by an explicit objective function, which is feasible for the whole l(2)-space. The classic egg-chicken loop in k-means has been simplified to a pure stochastic optimization procedure. The procedure of k-means becomes simpler and converges to a considerably better local …

Remote Vibration Estimation Using Displaced-Phase-Center Antenna Sar For Strong Clutter Environments, Justin B. Campbell, Francisco Pérez, Qi Wang, Balasubramaniam Santhanam, Ralf Dunkel, Armin W. Doerry, Thomas Atwood, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

It has been previously demonstrated that it is possible to perform remote vibrometry using synthetic aperture radar (SAR) in conjunction with the discrete fractional Fourier transform (DFrFT). Specifically, the DFrFT estimates the chirp parameters (related to the instantaneous acceleration of a vibrating object) of a slow-time signal associated with the SAR image. However, ground clutter surrounding a vibrating object introduces uncertainties in the estimate of the chirp parameter retrieved via the DFrFT method. To overcome this shortcoming, various techniques based on subspace decomposition of the SAR slow-time signal have been developed. Nonetheless, the effectiveness of these techniques is limited to …

Pollen Grains Recognition Based On Computer Vision Methods, Amar Idrees Daood

Theses and Dissertations

The classification of pollen grains is a main task in many disciplines including ecology, forensic sciences, allergy control, and oil exploration. In these application areas, visual inspection is the common method used for classifying pollen. However, recognition by visual inspection consumes much time and effort. Even though some level of automation exists, the automatic recognition of pollen grains remains an open problem. Current pollen-classification solutions rely on measurements of visual cues such as contour or texture. However, these features do not capture the visual complexity of information needed for discriminating among various species of pollen, especially when both a large-scale …

Speech Emotion Recognition Using Connectionist Models In A Tandem System, Mary Najafi

Theses and Dissertations

This article presents a tandem Speech Emotion Recognition (SER) system by which 8 archetypal emotions can be differentiated based upon two different types of acoustic features as inputs to Artificial Neural Network (ANN) models. The two types of features that are fed into the classifiers reveal the degree of excitement and pleasentness of speech. The author has implied the time-based characteristics of speech in the feature extraction method by monitoring the trend of local features through time. Thus, two global features are proposed that are derived from Teager Energy Operator (TEO)-based (T EOg) and spectral features, Mel-Frequency Cepstral Coeffcients (MF …

Optimizing The Use Of A Liquid Handling Robot To Conduct A High Throughput Forward Chemical Genetics Screen Of Arabidopsis Thaliana, B. Kirtley Amos, Victoria G. Pook, Seth Debolt

Horticulture Faculty Publications

Chemical genetics is increasingly being employed to decode traits in plants that may be recalcitrant to traditional genetics due to gene redundancy or lethality. However, the probability of a synthetic small molecule being bioactive is low; therefore, thousands of molecules must be tested in order to find those of interest. Liquid handling robotics systems are designed to handle large numbers of samples, increasing the speed with which a chemical library can be screened in addition to minimizing/standardizing error. To achieve a high-throughput forward chemical genetics screen of a library of 50,000 small molecules on Arabidopsis thaliana (Arabidopsis), protocols using a …

A Strategic Audit Of Chegg, Jacob Melcher

Honors Program: Senior Projects (Public)

The paper researches and discusses the strategy of Chegg in the past and future with regards to what was taught in UNL’s MNGT 495H course. The data was compiled from online resources including the company’s website and financials along with insights learned during an internship and interviews done in the Summer of 2016 and Spring of 2018. The insights of how Chegg went from a textbook rental company to the student learning hub it is today include experienced leaders, acquisitions and mergers, and being ahead of the curve in the industry. The final recommendation for Chegg’s strategy is to widen …

Comparative Study Of Deep Learning Models For Network Intrusion Detection, Brian Lee, Sandhya Amaresh, Clifford Green, Daniel Engels

SMU Data Science Review

In this paper, we present a comparative evaluation of deep learning approaches to network intrusion detection. A Network Intrusion Detection System (NIDS) is a critical component of every Internet connected system due to likely attacks from both external and internal sources. A NIDS is used to detect network born attacks such as Denial of Service (DoS) attacks, malware replication, and intruders that are operating within the system. Multiple deep learning approaches have been proposed for intrusion detection systems. We evaluate three models, a vanilla deep neural net (DNN), self-taught learning (STL) approach, and Recurrent Neural Network (RNN) based Long Short …

Comparative Study: Reducing Cost To Manage Accessibility With Existing Data, Claire Chu, Bill Kerneckel, Eric C. Larson, Nathan Mowat, Christopher Woodard

SMU Data Science Review

“Project Sidewalk” is an existing research effort that focuses on mapping accessibility issues for handicapped persons to efficiently plan wheelchair and mobile scooter friendly routes around Washington D.C. As supporters of this project, we utilized the data “Project Sidewalk” collected and used it to confirm predictions about where problem sidewalks exist based on real estate and crime data. We present a study that identifies correlations found between accessibility data and crime and housing statistics in the Washington D.C. metropolitan area. We identify the key reasons for increased accessibility and the issues with the current infrastructure management system. After a thorough …

Distributed Iterative Graph Processing Using Nosql With Data Locality, Ayam Pokhrel

LSU Master's Theses

A tremendous amount of data is generated every day from a wide range of sources such as social networks, sensors, and application logs. Among them, graph data is one type that represents valuable relationships between various entities. Analytics of large graphs has become an essential part of business processes and scientific studies because it leads to deep and meaningful insights into the related domain based on the connections between various entities. However, the optimal processing of large-scale iterative graph computations is very challenging due to the issues like fault tolerance, high memory requirement, parallelization, and scalability. Most of the contemporary …

Library Awesome Sauce Undergraduate Research, Jeremy Evert, Phillip Joe Fitzsimmons, Hector Lucas

Faculty Articles & Research

Library Awesome Sauce Undergraduate Research was a presentation at the 2018 CADRE Conference in Stillwater, OK. The presenters discussed their collaboration on a video project to film interviews of students giving progress reports about their software engineering projects. The videos were posted on the institutional repository.

The speakers discussed Student-Led research and the role that academic libraries play in facilitating student and faculty research and publishing for all disciplines on campus.

Correlated Network Of Networks Enhances Robustness Against Catastrophic Failures, Byungjoon Min, Muhua Zheng

Publications and Research

Networks in nature rarely function in isolation but instead interact with one another with a form of a network of networks (NoN). A network of networks with interdependency between distinct networks contains instability of abrupt collapse related to the global rule of activation. As a remedy of the collapse instability, here we investigate a model of correlated NoN. We find that the collapse instability can be removed when hubs provide the majority of interconnections and interconnections are convergent between hubs. Thus, our study identifies a stable structure of correlated NoN against catastrophic failures. Our result further suggests a plausible way …

Early Alert Of At-Risk Students: An Ontology-Driven Framework, Elias S. Lopez

Electrical and Computer Engineering ETDs

As higher education continues to adapt to the constantly shifting conditions that society places on institutions, the enigma of student attrition continues to trouble universities. Early alerts for students who are at-risk academically have been introduced as a method for solving student attrition at these institutions. Early alert systems are designed to provide students who are academically at-risk a prompt indication so that they may correct their performance and make progress towards successful semester completion. Many early alert systems have been introduced and implemented at various institutions with varying levels of success. Currently, early alert systems employ different techniques for …

A Route Less Traveled: Principals’ Perceptions Of Alternative Licensed Cte Teachers, Scott R. Bartholomew, Emma P. Bullock, Louis S. Nadelson

Faculty Publications

The shortage of teachers prepared to teach career and technical education (CTE) courses, or willing to work in certain locations (e.g. inner city, rural), has motivated the desire to explore solutions such as alternative routes to teacher licensure (ARL). Most ARL programs bypass colleges of education and provide a different approach to preparing individuals to teach, leaving many to wonder about the quality and knowledge of these teachers. Specific areas, such as CTE, have seen a large influx of ARL teachers in recent years. We sought to determine school principals’ perceptions of ARL CTE teachers. We found principal support for …

Representation Of Characters By Gender Across Video Game Covers Of Different Ratings, Alexandra Cassidy, Aaron Cornell, Emily Burgess, Stephen Burgess, Jeremy Evert

Student Research

This research was in response to the perception that females are under-represented in gaming culture. Pew Research Center (2015) found that both males and females thought more males played video games (60%). However, there is not a statistically significant difference in the percentage of males and females who have ever played video games (50% M 48% F). There is the perception that the advertising and production of video games contribute to the different stereotypes associated with men and women in gaming culture. According to research about gender and video game production, both male and female employees who work in the …

Cost-Effective Techniques For Continuous Integration Testing, Jingjing Liang

School of Computing: Dissertations, Theses, and Student Research

Continuous integration (CI) development environments allow software engineers to frequently integrate and test their code. While CI environments provide advantages, they also utilize non-trivial amounts of time and resources. To address this issue, researchers have adapted techniques for test case prioritization (TCP) and regression test selection (RTS) to CI environments.

To date, current TCP techniques under CI environments have operated on test suites, and have not achieved substantial improvements. In this thesis, we use a lightweight approach based on test suite failure and execution history, and “continuously” prioritizes commits that are waiting for execution in response to the arrival of …

Mechanical Characterization Of Polysilicon Mems: A Hybrid Tmcmc/Pod-Kriging Approach, Ramin Mirzazadeh, Saeed Eftekhar Azam, Stefano Mariani

Department of Civil and Environmental Engineering: Faculty Publications

Microscale uncertainties related to the geometry and morphology of polycrystalline silicon films, constituting the movable structures of micro electro-mechanical systems (MEMS), were investigated through a joint numerical/experimental approach. An on-chip testing device was designed and fabricated to deform a compliant polysilicon beam. In previous studies, we showed that the scattering in the input–output characteristics of the device can be properly described only if statistical features related to the morphology of the columnar polysilicon film and to the etching process adopted to release the movable structure are taken into account. In this work, a high fidelity finite element model of the …

Strategic Implications Of Blockchain, William R. Adams

Undergraduate Honors Theses

This thesis introduces blockchain, the underlying technology of cryptocurrencies such as Bitcoin, and discusses how best to conceptualize it relative to other technologies. Following an explanation of the fundamentals of blockchain, also known as the distributed ledger, I identify the characteristics of the technology. Building upon blockchain’s inherent strengths and limitations, I explore potential business applications of blockchain. Finally, I recommend that leaders continue to track the development and adoption of blockchain technology, even if they decide that implementing it does not align with their organization’s strategy at present.

Electrical And Material Properties Of Hydrothermally Grown Single Crystal (111) Uo2, Christina L. Dugan, George Glenn Peterson, Alyssa Mock, Christopher Young, J. Matthew Mann, Michael Nastasi, Mathias Schubert, Lu Wang, Wai-Ning Mei, Iori Tanabe, Peter A. Dowben, James Petrosky

Department of Electrical and Computer Engineering: Faculty Publications

The semiconductor and optical properties of UO₂ are investigated. The very long drift carrier lifetimes, obtained from current-voltage I(V) and capacitance-voltage C(V) measurements, along with the well-defined optical properties provide little evidence of an abundance of material defects away from the surface region. Schottky barrier formation may be possible, but very much dependent on the choice of contact and surface stoichiometry and we find that Ohmic contacts are in fact favored. Depth resolved photoemission provided evidence of a chemical shift at the surface. Density functional theory, with the Heyd-Scuseria-Ernzerhof (HSE) functional, indicates a band gap of a 2.19 eV …

Degradation Modeling And Rul Prediction Using Wiener Process Subject To Multiple Change Points And Unit Heterogeneity, Yuxin Wen, Jianguo Wu, Devashish Das, Tzu-Liang Bill Tseng

Engineering Faculty Articles and Research

Degradation modeling is critical for health condition monitoring and remaining useful life prediction (RUL). The prognostic accuracy highly depends on the capability of modeling the evolution of degradation signals. In many practical applications, however, the degradation signals show multiple phases, where the conventional degradation models are often inadequate. To better characterize the degradation signals of multiple-phase characteristics, we propose a multiple change-point Wiener process as a degradation model. To take into account the between-unit heterogeneity, a fully Bayesian approach is developed where all model parameters are assumed random. At the offline stage, an empirical two-stage process is proposed for model …

Multi-Objective Resource Provisioning In Network Function Virtualization Infrastructures, Diogo Oliveira

USF Tampa Graduate Theses and Dissertations

Network function virtualization (NFV) and software-dened networking (SDN) are two recent networking paradigms that strive to increase manageability, scalability, pro- grammability and dynamism. The former decouples network functions and hosting devices, while the latter decouples the data and control planes. As more and more service providers adopt these new paradigms, there is a growing need to address multi-failure conditions, particularly those arising from large-scale disaster events. Overall, addressing the virtual network function (VNF) placement and routing problem is crucial to deploy NFV surviv- ability. In particular, many studies have inspected non-survivable VNF provisioning, however no known work have proposed survivable/resilient …

Resampling Methods And Visualization Tools For Computer Performance Comparisons In The Presence Of Performance Variation, Samuel Oridge Irving

LSU Master's Theses

Performance variability, stemming from non-deterministic hardware and software behaviors or deterministic behaviors such as measurement bias, is a well-known phenomenon of computer systems which increases the difficulty of comparing computer performance metrics and is slated to become even more of a concern as interest in Big Data Analytics increases. Conventional methods use various measures (such as geometric mean) to quantify the performance of different benchmarks to compare computers without considering this variability which may lead to wrong conclusions. In this paper, we propose three resampling methods for performance evaluation and comparison: a randomization test for a general performance comparison between …

Crawling Tor's Hidden Services And Depicting Their Interconnectivity, John-Luke N. Navarro

Honors Theses

The Tor network is a popular online privacy platform that enables anonymous browsing, but is also notorious for the vast number of illicit marketplaces, goods and services available to users. Tor's protocols also secure hosted websites, known as hidden services, against unwanted tracking and location. Tor has attracted the attention of law enforcement agencies, who are interested in hidden service data analysis. However, little large-scale analysis is currently performed. To help address this issue, I constructed two tools. A specialized web crawler downloads bulk page-content from Tor's hidden services. This program crawls the Tor Network broadly, securely, and with more …