Computer Engineering Commons^™

Efficiency Improvement Of Fault-Tolerant Three-Level Power Converters, Ramin Katebi, Jiangbiao He, Waqar A. Khan, Nathan Weise

Electrical and Computer Engineering Faculty Research and Publications

Fault-tolerant power converters play a critical role in the transportation electrification. However, fault-tolerant operation, high efficiency, and low cost usually result in design criteria that have conflicting constraints and goals. The majority of the fault-tolerant power converter topologies presented in the literature confirm these conflicts. In this paper, three types of fault-tolerant neutral-point clamped (NPC) converters are investigated. Various modulation strategies are explored to reduce the losses of the redundant phase leg. The simulation and experimental results show that the Switching Frequency Optimal Phase opposition Disposition modulation strategy is the most effective approach in minimizing the losses in the redundant …

Detection And Quantification Of Multi-Analyte Mixtures Using A Single Sensor And Multi-Stage Data-Weighted Rlse, Karthick Sothivelr, Florian Bender, Fabien Josse, Edwin E. Yaz, Antonio J. Ricco

Electrical and Computer Engineering Faculty Research and Publications

This work reports the development and experimental verification of a sensor signal processing technique for online identification and quantification of aqueous mixtures of benzene, toluene, ethylbenzene, xylenes (BTEX) and 1, 2, 4-trimethylbenzene (TMB) at ppb concentrations using time-dependent frequency responses from a single polymer-coated shear-horizontal surface acoustic wave sensor. Signal processing based on multi-stage exponentially weighted recursive leastsquares estimation (EW-RLSE) is utilized for estimating the concentrations of the analytes in the mixture that are most likely to have produced a given sensor response. The initial stages of EW-RLSE are used to eliminate analyte(s) that are erroneously identified as present in …

Stochastic Search Methods For Mobile Manipulators, Amoako-Frimpong Samuel Yaw, Matthew Messina, Henry P. Medeiros, Jeremy Marvel, Roger Bostelman

Electrical and Computer Engineering Faculty Research and Publications

Mobile manipulators are a potential solution to the increasing need for additional flexibility and mobility in industrial applications. However, they tend to lack the accuracy and precision achieved by fixed manipulators, especially in scenarios where both the manipulator and the autonomous vehicle move simultaneously. This paper analyzes the problem of dynamically evaluating the positioning error of mobile manipulators. In particular, it investigates the use of Bayesian methods to predict the position of the end-effector in the presence of uncertainty propagated from the mobile platform. The precision of the mobile manipulator is evaluated through its ability to intercept retroreflective markers using …

Gender Effects Of Robotics Programs On Stem-Related Self-Efficacy Of High School Students, Sandra Hall-Lay

Walden Dissertations and Doctoral Studies

Lack of STEM-related self-efficacy has impeded the growth of women in STEM fields. Out of school (OST) robotics programs and other STEM-related OST programs provide secondary students with opportunities to work in groups, brainstorm, and formulate ideas that require communication and teamwork. The purpose of this quantitative, quasi-experimental study was to compare STEM-related self-efficacy scores among male and female students who participated in OST robotics programs or other OST STEM-related programming. Independent variables were type of OST STEM program and gender. The dependent variable was students' STEM-related self-efficacy as measured by the Coping Self-Efficacy Scale. Responses from 149 students in …

Developing A Recurrent Neural Network With High Accuracy For Binary Sentiment Analysis, Kevin Cunanan

CMC Senior Theses

Sentiment analysis has taken on various machine learning approaches in order to optimize accuracy, precision, and recall. However, Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) account for the context of a sentence by using previous predictions as additional input for future sentence predictions. Our approach focused on developing an LSTM RNN that could perform binary sentiment analysis for positively and negatively labeled sentences. In collaboration with Mariam Salloum, I developed a collection of programs to classify individual sentences as either positive or negative. This paper additionally looks into machine learning, neural networks, data preprocessing, implementation, and resulting comparisons.

Developing An Energy Efficient Real-Time System, Aamir Aarif Khan

Masters Theses

"Increasing number of battery operated devices creates a need for energy-efficient real-time operating system for such devices. Designing a truly energy-efficient system is a multi-staged effort; this thesis consists of three main tasks that address different aspects of energy efficiency of a real-time system (RTS).

The first chapter introduces an energy-efficient algorithm that alternates processor frequency using DVFS to schedule tasks on cores. Speed profiles is calculated for every task that gives information about how long a task would run for and at what processor speed. We pair tasks with similar speed profiles to give us a resultant merged speed …

Machine Learning Techniques Implementation In Power Optimization, Data Processing, And Bio-Medical Applications, Khalid Khairullah Mezied Al-Jabery

Doctoral Dissertations

"The rapid progress and development in machine-learning algorithms becomes a key factor in determining the future of humanity. These algorithms and techniques were utilized to solve a wide spectrum of problems extended from data mining and knowledge discovery to unsupervised learning and optimization. This dissertation consists of two study areas. The first area investigates the use of reinforcement learning and adaptive critic design algorithms in the field of power grid control. The second area in this dissertation, consisting of three papers, focuses on developing and applying clustering algorithms on biomedical data. The first paper presents a novel modelling approach for …

Epithelium Detection And Cervical Intraepithelial Neoplasia Classification In Digitized Histology Images, Sri Venkata Ravitej Addanki

Masters Theses

“Cervical cancer is one of the most deadly cancers faced by women. It is the second leading cause of cancer death in women aged 20 to 39 years. In order to detect cancer at early stages, pathologists analyze the epithelium region from the cervical histology images. These histology images have a pre-cervical cancer condition called cervical intraepithelial neoplasia (CIN) determined by pathologists. This study deals with automating the process of epithelium detection and epithelium CIN classification in digitized histology images. For epithelium detection, the objective is to detect epithelium regions in microscopy images from non-epithelium regions and background. convolutional neural …

A Stochastic Petri Net Reverse Engineering Methodology For Deep Understanding Of Technical Documents, Giorgia Rematska

Browse all Theses and Dissertations

Systems Reverse Engineering has gained great attention over time and is associated with numerous different research areas. The importance of this research derives from several technological necessities. Security analysis and learning purposes are two of them and can greatly benefit from reverse engineering. More specifically, reverse engineering of technical documents for deeper automatic understanding is a research area where reverse engineering can contribute a lot. In this PhD dissertation we develop a novel reverse engineering methodology for deep understanding of architectural description of digital hardware systems that appear in technical documents. Initially, we offer a survey on reverse engineering of …

Building An Abstract-Syntax-Tree-Oriented Symbolic Execution Engine For Php Programs, Jin Huang

Browse all Theses and Dissertations

This thesis presents the design, implementation, and evaluation of an abstract-syntax-tree-oriented symbolic execution engine for the PHP programming language. As a symbolic execution engine, our system emulate the execution of a PHP program by assuming that all inputs are with symbolic rather than concrete values. While our system inherits the basic definition of symbolic execution, it fundamentally differs from existing symbolic execution implementations that mainly leverage intermediate representation (IRs) to operate. Specifically, our system directly takes the abstract syntax tree (AST) of a program as input and subsequently interprets this AST. Performing symbolic execution using AST offers unique advantages. First, …

Slim Embedding Layers For Recurrent Neural Language Models, Zhongliang Li

Browse all Theses and Dissertations

Recurrent neural language (RNN) models are the state-of-the-art method for language modeling. When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of these type of models. We introduce a simple space compression method that stochastically shares the structured parameters at both the input and output embedding layers of RNN models to significantly reduce the size of model parameters, but still compactly represents the original input and the output embedding layers. The method is easy to implement and tune. Experiments on several data sets show that the new method achieves …

Masquerading Techniques In Ieee 802.11 Wireless Local Area Networks, Omar Nakhila

Electronic Theses and Dissertations

The airborne nature of wireless transmission offers a potential target for attackers to compromise IEEE 802.11 Wireless Local Area Network (WLAN). In this dissertation, we explore the current WLAN security threats and their corresponding defense solutions. In our study, we divide WLAN vulnerabilities into two aspects, client, and administrator. The client-side vulnerability investigation is based on examining the Evil Twin Attack (ETA) while our administrator side research targets Wi-Fi Protected Access II (WPA2). Three novel techniques have been presented to detect ETA. The detection methods are based on (1) creating a secure connection to a remote server to detect the …

Application For Position And Load Reference Generation Of A Simulated Mechatronic Chain, Florentin Smarandache, V. Vladareanu, S.B. Cononovici, M. Migdalovici, H. Wang, Y. Feng

Branch Mathematics and Statistics Faculty and Staff Publications

The paper presents the position and load reference generation for a motor stand simulating a mechatronic chain, in this case a three degree of freedom robot leg. The task is accomplished using three PLC controlled motors in position as the robot joint actuators coupled with three controlled in torque, simulating the load at each simulation time-step. The paper briefly discusses the mathematical model and presents the visual interface used in the simulation, which is then to be further integrated into a virtual environment robot control application.

Enhancing Cognitive Algorithms For Optimal Performance Of Adaptive Networks, Hector Lugo-Cordero

Electronic Theses and Dissertations

This research proposes to enhance some Evolutionary Algorithms in order to obtain optimal and adaptive network configurations. Due to the richness in technologies, low cost, and application usages, we consider Heterogeneous Wireless Mesh Networks. In particular, we evaluate the domains of Network Deployment, Smart Grids/Homes, and Intrusion Detection Systems. Having an adaptive network as one of the goals, we consider a robust noise tolerant methodology that can quickly react to changes in the environment. Furthermore, the diversity of the performance objectives considered (e.g., power, coverage, anonymity, etc.) makes the objective function non-continuous and therefore not have a derivative. For these …

Energy Efficient And Secure Wireless Sensor Networks Design, Afraa Attiah

Electronic Theses and Dissertations

Wireless Sensor Networks (WSNs) are emerging technologies that have the ability to sense, process, communicate, and transmit information to a destination, and they are expected to have significant impact on the efficiency of many applications in various fields. The resource constraint such as limited battery power, is the greatest challenge in WSNs design as it affects the lifetime and performance of the network. An energy efficient, secure, and trustworthy system is vital when a WSN involves highly sensitive information. Thus, it is critical to design mechanisms that are energy efficient and secure while at the same time maintaining the desired …

Joint Optimization Of Illumination And Communication For A Multi-Element Vlc Architecture, Sifat Ibne Mushfique

Electronic Theses and Dissertations

Because of the ever increasing demand wireless data in the modern era, the Radio Frequency (RF) spectrum is becoming more congested. The remaining RF spectrum is being shrunk at a very heavy rate, and spectral management is becoming more difficult. Mobile data is estimated to grow more than 10 times between 2013 and 2019, and due to this explosion in data usage, mobile operators are having serious concerns focusing on public Wireless Fidelity (Wi-Fi) and other alternative technologies. Visible Light Communication (VLC) is a recent promising technology complementary to RF spectrum which operates at the visible light spectrum band (roughly …

Bridging The Gap Between Application And Solid-State-Drives, Jian Zhou

Electronic Theses and Dissertations

Data storage is one of the important and often critical parts of the computing system in terms of performance, cost, reliability, and energy. Numerous new memory technologies, such as NAND flash, phase change memory (PCM), magnetic RAM (STT-RAM) and Memristor, have emerged recently. Many of them have already entered the production system. Traditional storage optimization and caching algorithms are far from optimal because storage I/Os do not show simple locality. To provide optimal storage we need accurate predictions of I/O behavior. However, the workloads are increasingly dynamic and diverse, making the long and short time I/O prediction challenge. Because of …

Real-Time Sil Emulation Architecture For Cooperative Automated Vehicles, Nitish Gupta

Electronic Theses and Dissertations

This thesis presents a robust, flexible and real-time architecture for Software-in-the-Loop (SIL) testing of connected vehicle safety applications. Emerging connected and automated vehicles (CAV) use sensing, communication and computing technologies in the design of a host of new safety applications. Testing and verification of these applications is a major concern for the automotive industry. The CAV safety applications work by sharing their state and movement information over wireless communication links. Vehicular communication has fueled the development of various Cooperative Vehicle Safety (CVS) applications. Development of safety applications for CAV requires testing in many different scenarios. However, the recreation of test …

A Game-Theoretic Model For Regulating Freeriding In Subsidy-Based Pervasive Spectrum Sharing Markets, Mostafizur Rahman

Electronic Theses and Dissertations

Cellular spectrum is a limited natural resource becoming scarcer at a worrisome rate. To satisfy users' expectation from wireless data services, researchers and practitioners recognized the necessity of more utilization and pervasive sharing of the spectrum. Though scarce, spectrum is underutilized in some areas or within certain operating hours due to the lack of appropriate regulatory policies, static allocation and emerging business challenges. Thus, finding ways to improve the utilization of this resource to make sharing more pervasive is of great importance. There already exists a number of solutions to increase spectrum utilization via increased sharing. Dynamic Spectrum Access (DSA) …

Automated Optical Mark Recognition Scoring System For Multiple-Choice Questions, Murtadha Alomran

Theses: Doctorates and Masters

Multiple-choice questions are one of the questions commonly used in assessments. It is widely used because this type of examination can be an effective and reliable way to examine the level of student’s knowledge. So far, this type of examination can either be marked by hand or with specialised answer sheets and scanning equipment. There are specialised answer sheets and scanning equipment to mark multiple-choice questions automatically. However, these are expensive, specialised and restrictive answer sheets and optical mark recognition scanners.

This research aims to design and implement a multiple-choice answer sheet and a reliable image processing-based scoring system that …