Computer Engineering Commons^™

A Survey Of Three-Dimensional Sound And Its Applications, Andrew Topping

Capstone Projects and Master's Theses

This research project seeks to develop a foundation of knowledge about three-dimensional sound (3-D sound) and its utilization across various media. Topics covered include the techniques by which 3-D sound is accomplished, its departures from the standard paradigm of stereophonic audio, the range of creative and engineering considerations within 3-D contexts and examinations of existing 3-D audio applications.

Development Of The Codebase For Ece Design: Smartwatch Device And App For Continuous Glucose Monitoring, Keelin J. Becker-Wheeler

Honors Scholar Theses

This honors thesis describes the development of the codebase for the 2018 University of Connecticut ECE Senior Design project titled "Smartwatch Device and App for Continuous Glucose Monitoring''. The goal for the senior design project is to remove the dependencies imposed by a previously-designed prototype of a glucose-monitoring smartwatch, by creating a new custom device without those dependencies. Development of the new codebase involves splitting the tasks of an Arduino codebase into a number of logical components that are then implemented in C. This new codebase makes substantial improvements to the overall program structure and organization, as well as numerous …

Security Analysis Of The Uconn Husky One Card, Trevor Phillips

Honors Scholar Theses

The “Husky One Card” is the name given to student IDs at the University of Connecticut. It can identify students, faculty, and staff in a variety of situations. The One Card is used for meal plans, Husky Bucks (an equivalent of money, but valid only in the Storrs area), residence hall/ university facility access, and student health services. The current Husky One Card consists of a picture identification on the front and a standard 1-dimensional barcode and 3-track magnetic strip on the back.

The goal of this thesis is to investigate the feasibility of cloning Husky One Cards, the ease …

Handwritten Digit Recognition By Multi-Class Support Vector Machines, Yu Wang

Graduate Theses/Dissertations

Support Vector Machine(SVM) is a widely-used tool for pattern classification problems. The main idea behind SVM is to separate two different groups with a hyperplane which makes the margin of these two groups maximized. It doesn't require any knowledge about the object we are focused on, since it can catch the features automatically. The idea of SVM can be easily generalized to nonlinear model by a mapping from the original space to a high-dimensional feature space, and they construct a max-margin linear classifier in the high dimensional feature space.

This thesis will investigate the basic idea of SVM and apply …

Securing Soft Ips Against Hardware Trojan Insertion, Thao Phuong Le

Graduate Theses and Dissertations

Due to the increasing complexity of hardware designs, third-party hardware Intellectual Property (IP) blocks are often incorporated in order to alleviate the burden on hardware designers. However, the prevalence use of third-party IPs has raised security concerns such as Trojans inserted by attackers. Hardware Trojans in these soft IPs are extremely difficult to detect through functional testing and no single detection methodology has been able to completely address this issue. Based on a Register-Transfer Level (RTL) and gate-level soft IP analysis method named Structural Checking, this dissertation presents a hardware Trojan detection methodology and tool by detailing the implementation of …

Automatic Speech Recognition Adaptation For Various Noise Levels, Azhar Sabah Abdulaziz

Theses and Dissertations

The automatic speech recognition (ASR) is a set of complicated algorithms that convert the intended spoken utterance into a textual form. Acoustic features, which are extracted from the speech signal, are matched against a trained network of linguistic and acoustic models. The ASR performance is degraded significantly when the ambient noise is different than that of the training data. Many approaches have been introduced to address this problem with various degrees of complexity and improvement rates. The general pattern of solving this issue lies in three categories: empowering features, train a general acoustic model and transform models to match noisy …

An Empirical Study On The Recovery Speed Of Usb Flash Drives Utilizing Raid-5 Compared To Hdds And Ssds, Joshua Manuel Martins

Honors Theses

Since their creation and implementation, storage drives have undergone and continue to undergo drastic changes in speed, size, and reliability. The original storage drives, known as hard disk drives (HDDs), are constructed using moving parts. The second modern type of storage drives, known as solid state drives (SSDs), are constructed using a series of silicon chips that utilize no moving parts. The third and most recent innovation in storage drives, known as USB flash drives (USBs), use only a single silicon chip to provide storage which grants them the smallest form factor of the three drive types.

This study compared …

Consensus Ensemble Approaches Improve De Novo Transcriptome Assemblies, Adam Voshall

School of Computing: Dissertations, Theses, and Student Research

Accurate and comprehensive transcriptome assemblies lay the foundation for a range of analyses, such as differential gene expression analysis, metabolic pathway reconstruction, novel gene discovery, or metabolic flux analysis. With the arrival of next-generation sequencing technologies it has become possible to acquire the whole transcriptome data rapidly even from non-model organisms. However, the problem of accurately assembling the transcriptome for any given sample remains extremely challenging, especially in species with a high prevalence of recent gene or genome duplications, those with alternative splicing of transcripts, or those whose genomes are not well studied. This thesis provides a detailed overview of …

Application Of Cosine Similarity In Bioinformatics, Srikanth Maturu

School of Computing: Dissertations, Theses, and Student Research

Finding similar sequences to an input query sequence (DNA or proteins) from a sequence data set is an important problem in bioinformatics. It provides researchers an intuition of what could be related or how the search space can be reduced for further tasks. An exact brute-force nearest-neighbor algorithm used for this task has complexity O(m * n) where n is the database size and m is the query size. Such an algorithm faces time-complexity issues as the database and query sizes increase. Furthermore, the use of alignment-based similarity measures such as minimum edit distance adds an additional complexity to the …

Horse Racing Prediction Using Graph-Based Features., Mehmet Akif Gulum

Electronic Theses and Dissertations

This thesis presents an applied horse racing prediction using graph based features on a set of horse races data. We used artificial neural network and logistic regression models to train then test to prediction without graph based features and with graph based features. This thesis can be explained in 4 main parts. Collect data from a horse racing website held from 2015 to 2017. Train data to using predictive models and make a prediction. Create a global directed graph of horses and extract graph-based features (Core Part) . Add graph based features to basic features and train to using same …

Skill Builder: Assistive Technology For Developing Skill And Habits, Aaron Kay

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The Skill Builder application is assistive technology for helping individuals build skills through reminders and self-reporting feedback. The application has been built to support Android and iOS devices and followed a user-centric design methodology. Skill Builder’s architecture and development processes are set forth using cross-platform development environments and a native software development kit for the three different versions of the application that were built. The strengths and weaknesses of each of the platforms are explored.

Several studies have been proposed for helping individuals with different needs learn the skills to cope with their challenges. Applications of Skill Builder include students …

Authentication Via Openathens: Implementing A Single Sign-On Solution For Primo, Alma, And Ezproxy, Travis Clamon

ETSU Faculty Works

OpenAthens is a hosted identity and access management service that provides a streamlined solution for implementing single sign-on authentication. This presentation will outline the steps East Tennessee State University took to configure OpenAthens authentication across the Alma, Primo, and EZproxy platforms. We will give a brief overview of the internal configurations related to LDAP integration, allocating electronic resources, and selectively assigning permissions. Finally, we will share our experiences with OpenAthens including support, vendor adoption, and end user benefits.

Machine Learning For Omics Data Analysis., Ameni Trabelsi

Electronic Theses and Dissertations

In proteomics and metabolomics, to quantify the changes of abundance levels of biomolecules in a biological system, multiple sample analysis steps are involved. The steps include mass spectrum deconvolution and peak list alignment. Each analysis step introduces a certain degree of technical variation in the abundance levels (i.e. peak areas) of those molecules. Some analysis steps introduce technical variations that affect the peak areas of all molecules equally while others affect the peak areas of a subset of molecules with varying degrees. To correct these technical variations, some existing normalization methods simply scale the peak areas of all molecules detected …

Maintainability Analysis Of Mining Trucks With Data Analytics., Abdulgani Kahraman

Electronic Theses and Dissertations

The mining industry is one of the biggest industries in need of a large budget, and current changes in global economic challenges force the industry to reduce its production expenses. One of the biggest expenditures is maintenance. Thanks to the data mining techniques, available historical records of machines’ alarms and signals might be used to predict machine failures. This is crucial because repairing machines after failures is not as efficient as utilizing predictive maintenance. In this case study, the reasons for failures seem to be related to the order of signals or alarms, called events, which come from trucks. The …

End-To-End Learning Framework For Circular Rna Classification From Other Long Non-Coding Rnas Using Multi-Modal Deep Learning., Mohamed Chaabane

Electronic Theses and Dissertations

Over the past two decades, a circular form of RNA (circular RNA) produced from splicing mechanism has become the focus of scientific studies due to its major role as a microRNA (miR) ac tivity modulator and its association with various diseases including cancer. Therefore, the detection of circular RNAs is a vital operation for continued comprehension of their biogenesis and purpose. Prediction of circular RNA can be achieved by first distinguishing non-coding RNAs from protein coding gene transcripts, separating short and long non-coding RNAs (lncRNAs), and finally pre dicting circular RNAs from other lncRNAs. However, available tools to distinguish circular …

Robust Fuzzy Clustering For Multiple Instance Regression., Mohamed Trabelsi

Electronic Theses and Dissertations

Multiple instance regression (MIR) operates on a collection of bags, where each bag contains multiple instances sharing an identical real-valued label. Only few instances, called primary instances, contribute to the bag labels. The remaining instances are noise and outliers observations. The goal in MIR is to identify the primary instances within each bag and learn a regression model that can predict the label of a previously unseen bag. In this thesis, we introduce an algorithm that uses robust fuzzy clustering with an appropriate distance to learn multiple linear models from a noisy feature space simultaneously. We show that fuzzy memberships …

A Framework For Cardio-Pulmonary Resuscitation (Cpr) Scene Retrieval From Medical Simulation Videos Based On Object And Activity Detection., Anju Panicker Madhusoodhanan Sathik

Electronic Theses and Dissertations

In this thesis, we propose a framework to detect and retrieve CPR activity scenes from medical simulation videos. Medical simulation is a modern training method for medical students, where an emergency patient condition is simulated on human-like mannequins and the students act upon. These simulation sessions are recorded by the physician, for later debriefing. With the increasing number of simulation videos, automatic detection and retrieval of specific scenes became necessary. The proposed framework for CPR scene retrieval, would eliminate the conventional approach of using shot detection and frame segmentation techniques. Firstly, our work explores the application of Histogram of Oriented …

Network Science Algorithms For Mobile Networks., Heba Mohamed Elgazzar

Electronic Theses and Dissertations

Network Science is one of the important and emerging fields in computer science and engineering that focuses on the study and analysis of different types of networks. The goal of this dissertation is to design and develop network science algorithms that can be used to study and analyze mobile networks. This can provide essential information and knowledge that can help mobile networks service providers to enhance the quality of the mobile services. We focus in this dissertation on the design and analysis of different network science techniques that can be used to analyze the dynamics of mobile networks. These techniques …

Asynchronous Circuit Stacking For Simplified Power Management, Andrew Lloyd Suchanek

Graduate Theses and Dissertations

As digital integrated circuits (ICs) continue to increase in complexity, new challenges arise for designers. Complex ICs are often designed by incorporating multiple power domains therefore requiring multiple voltage converters to produce the corresponding supply voltages. These converters not only take substantial on-chip layout area and/or off-chip space, but also aggregate the power loss during the voltage conversions that must occur fast enough to maintain the necessary power supplies. This dissertation work presents an asynchronous Multi-Threshold NULL Convention Logic (MTNCL) “stacked” circuit architecture that alleviates this problem by reducing the number of voltage converters needed to supply the voltage the …

Service Quality Assessment For Cloud-Based Distributed Data Services, Arun Adiththan

Dissertations, Theses, and Capstone Projects

The issue of less-than-100% reliability and trust-worthiness of third-party controlled cloud components (e.g., IaaS and SaaS components from different vendors) may lead to laxity in the QoS guarantees offered by a service-support system S to various applications. An example of S is a replicated data service to handle customer queries with fault-tolerance and performance goals. QoS laxity (i.e., SLA violations) may be inadvertent: say, due to the inability of system designers to model the impact of sub-system behaviors onto a deliverable QoS. Sometimes, QoS laxity may even be intentional: say, to reap revenue-oriented benefits by cheating on resource allocations and/or …

Critical-Point Model Dielectric Function Analysis Of Wo3 Thin Films Deposited By Atomic Layer Deposition Techniques, Ufuk Kılıç, Derek Sekora, Alyssa Mock, Rafał Korlacki, Elena M. Echeverría, Natale J. Ianno, Eva Schubert, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

WO₃ thin films were grown by atomic layer deposition and spectroscopic ellipsometry data gathered in the photon energy range of 0.72-8.5 eV and from multiple samples was utilized to determine the frequency dependent complex-valued isotropic dielectric function for WO₃. We employ a critical-point model dielectric function analysis and determine a parameterized set of oscillators and compare the observed critical-point contributions with the vertical transition energy distribution found within the band structure of WO₃ calculated by density functional theory. We investigate surface roughness with atomic force microscopy and compare to ellipsometric determined effective roughness layer thickness.

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 …