Computer Engineering Commons^™

Optimizing The Placement Of Multiple Uav--Lidar Units Under Road Priority And Resolution Requirements, Zachary Michael Osterwisch

Masters Theses

"Real-time road traffic information is crucial for intelligent transportation systems (ITS) applications, like traffic navigation or emergency response management, but acquiring such data is tremendously challenging in practice because of the high costs and inefficient placement of sensors. Some modern ITS applications contribute to this problem by equipping vehicles with multiple light detection and ranging (LiDAR) sensors, which are expensive and gather data inefficiently; one solution that avoids vehicle-mounted LiDAR acquisition has been to install elevated LiDAR instruments along roadways, but this approach remains unrefined. The eventual development of sixth-generation (6G) wireless communication will enable new, creative solutions to solve …

Incorporating Novel Sensors For Reading Human Health State And Motion Intent Into Real-Time Computing Systems, Adam Sawyer

Masters Theses

"Integrating sensors that read states of the human body into everyday life is an increasing desire, especially with the rise of deep learning which requires vast stores of data to make predictions. This work explores integrating these sensors into the human experience through two methods and recording the results. The first of these methods integrates a MXene based field-effect transistor sensor for the 2019-nCov spike protein with a mobile app. This allows the user to read how saturated their breath is with Covid-19. The second method integrates 3D-printed pressure sensors, and a motion capture system, into a glove to read …

A Hybrid Framework For Critical Infrastructures Interdependency Modeling, Simulation, And Analysis, David Corder Hinton

Masters Theses

"Flow system models, also known as flow network models, encompass vastly complex, ever-expanding problem sets which comprise the foundation for maintenance, operation, and improvement of critical infrastructures around the world. The stable operation of these vast critical infrastructures is fundamental to the continued advancement of modern society. These infrastructures are tightly interdependent and vulnerable to interruption by both natural circumstance and malicious targeting. This necessitates representation of such critical infrastructures and their multi-domain interdependencies in defense focused constructive and virtual simulation environments as a matter of national interest and security. By breadth exploration of the problem space, this work body …

Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Charles Dobbins

Masters Theses

"This work proposes an intelligent recommender approach to facilitate personalized education and help students in planning their path to graduation. The original research contribution of this work is to develop a recommender approach that pervasively personalizes and optimizes a student’s path to graduation by accounting for the student’s career interests and academic background. The approach is a multi-objective optimization problem, subject to institutional constraints, with the goal of optimizing the graduation path with respect to one or more criteria, such as time-to-graduation, credit hours taken, and alignment with student’s career interests. The efficacy of the approach is illustrated and verified …

Neural Network Supervised And Reinforcement Learning For Neurological, Diagnostic, And Modeling Problems, Donald Wunsch Iii

Masters Theses

“As the medical world becomes increasingly intertwined with the tech sphere, machine learning on medical datasets and mathematical models becomes an attractive application. This research looks at the predictive capabilities of neural networks and other machine learning algorithms, and assesses the validity of several feature selection strategies to reduce the negative effects of high dataset dimensionality. Our results indicate that several feature selection methods can maintain high validation and test accuracy on classification tasks, with neural networks performing best, for both single class and multi-class classification applications. This research also evaluates a proof-of-concept application of a deep-Q-learning network (DQN) to …

Topological Biclustering Artmap, Raghu Yelugam

Masters Theses

”Detection of gene mutations is central for assessing genetic factors affecting disease predisposition, genetic causes of a particular disease, and gene-targeted treatment. DNA microarray methods are widely used to detect mutations by contrasting the expression levels of thousands of genes together under varying experimental conditions. The experimental conditions could be diseased cell states compared with the normal cell states. Biclustering, a robust exploratory data analysis tool, can be applied to microarray data to detect subsets of genes that co-express highly only for a subset of experimental conditions. Such detection is crucial for gaining insights into gene regulatory networks, differential gene …

Controlled Switching In Kalman Filtering And Iterative Learning Controls, He Li

Masters Theses

“Switching is not an uncommon phenomenon in practical systems and processes, for examples, power switches opening and closing, transmissions lifting from low gear to high gear, and air planes crossing different layers in air. Switching can be a disaster to a system since frequent switching between two asymptotically stable subsystems may result in unstable dynamics. On the contrary, switching can be a benefit to a system since controlled switching is sometimes imposed by the designers to achieve desired performance. This encourages the study of system dynamics and performance when undesired switching occurs or controlled switching is imposed. In this research, …

Light Touch Based Virtual Cane For Balance Assistance During Standing, Sindhu Reddy Alluri

Masters Theses

"Can additional information about one's body kinematics provided through hands improve human balance? Light-Touch (LT) through hands helps improve balance in a wide range of populations, both healthy and impaired. The force is too small to provide any meaningful mechanical assistance -- rather, it is suggested that the additional sensory information through hands helps the body improve balance.

To investigate the potential for improving human balance through biofeedback through hands, we developed a Virtual Cane (VC) for balance assistance during standing. The VC mimics the physical cane's function of providing information about one's body in space. Balance experiments on 10 …

Routing Algorithm For The Ground Team In Transmission Line Inspection Using Unmanned Aerial Vehicle, Yu Li

Masters Theses

"With the rapid development of robotics technology, robots are increasingly used to conduct various tasks by utility companies. An unmanned aerial vehicle (UAV) is an efficient robot that can be used to inspect high-voltage transmission lines. UAVs need to stay within a data transmission range from the ground station and periodically land to replace the battery in order to ensure that the power system can support its operation. A routing algorithm must be used in order to guide the motion and deployment of the ground station while using UAV in transmission line inspection. Most existing routing algorithms are dedicated to …

Less Is More: Beating The Market With Recurrent Reinforcement Learning, Louis Kurt Bernhard Steinmeister

Masters Theses

"Multiple recurrent reinforcement learners were implemented to make trading decisions based on real and freely available macro-economic data. The learning algorithm and different reinforcement functions (the Differential Sharpe Ratio, Differential Downside Deviation Ratio and Returns) were revised and the performances were compared while transaction costs were taken into account. (This is important for practical implementations even though many publications ignore this consideration.) It was assumed that the traders make long-short decisions in the S&P500 with complementary 3-month treasury bill investments. Leveraged positions in the S&P500 were disallowed. Notably, the Differential Sharpe Ratio and the Differential Downside Deviation Ratio are risk …

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 …

Precise Energy Efficient Scheduling Of Mixed-Criticality Tasks & Sustainable Mixed-Criticality Scheduling, Sai Sruti

Masters Theses

"In this thesis, the imprecise mixed-criticality model (IMC) is extended to precise scheduling of tasks, and integrated with the dynamic voltage and frequency scaling (DVFS) technique to enable energy minimization. The challenge in precise scheduling of MC systems is to simultaneously guarantee the timing correctness for all tasks, hi and lo, under both pessimistic and optimistic (less pessimistic) assumptions. To the best of knowledge this is the first work to address the integration of DVFS energy conserving techniques with precise scheduling of lo-tasks of the MC model.

In this thesis, the utilization based schedulability tests and sufficient conditions for such …

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 …

Analysis Of Outsourcing Data To The Cloud Using Autonomous Key Generation, Mortada Abdulwahed Aman

Masters Theses

"Cloud computing, a technology that enables users to store and manage their data at a low cost and high availability, has been emerging for the past few decades because of the many services it provides. One of the many services cloud computing provides to its users is data storage. The majority of the users of this service are still concerned to outsource their data due to the integrity and confidentiality issues, as well as performance and cost issues, that come along with it. These issues make it necessary to encrypt data prior to outsourcing it to the cloud. However, encrypting …

Predicting The Impact Of Data Corruption On The Operation Of Cyber-Physical Systems, Erik David Burgdorf

Masters Theses

"Cyber-physical systems, where computing and communication are used to fortify and streamline the operation of a physical infrastructure, now comprise the foundation of much of modern critical infrastructure. These systems are typically large in scale and highly interconnected, and span application domains from power and water distribution to autonomous vehicle control and collaborative robotics. Intelligent decision support in these systems is heavily reliant on the availability of sufficient and sufficiently correct data. Failure or malfunction of these systems can have devastating consequences in terms of public safety, financial losses, or both.

The research described in this thesis aims to predict …

Novel Approaches For Efficient Stochastic Computing, Ramu Seva

Masters Theses

"This thesis is comprised of two papers, where the first paper presents a novel approach for parallel implementation of SC using FPGA (Field Programmable Gate Array). This paper makes use of the distributed memory elements of FPGAs (i.e., look-up-tables -LUTs) to achieve this. An attempt has been made to build the stochastic number generators (SNGs) by using the proposed LUT approach. The construction of these SNGs has been influenced by the Quasi-random number sequences, which provide the advantage of reducing the random fluctuations present in the pseudo-random number generators such as LFSR (Linear Feedback Shift Register) as well as the …

Using Adaptive Thresholding And Skewness Correction To Detect Gray Areas In Melanoma In Situ Images, Jason R. Hagerty

Masters Theses

"The incidence of melanoma in situ (MIS) is growing significantly. Detection at the MIS stage provides the highest cure rate for melanoma, but reliable detection of MIS with dermoscopy alone is not yet possible. Adjunct dermoscopic instrumentation using digital image analysis may allow more accurate detection of MIS. Gray areas are a critical component of MIS diagnosis, but automatic detection of these areas remains difficult because similar gray areas are also found in benign lesions. This paper proposes a novel adaptive thresholding technique for automatically detecting gray areas specific to MIS. The proposed model uses only MIS dermoscopic images to …

Numerical Analysis Of Flexural Slip During Viscoelastic Buckle Folding, Davi Rodrigues Damasceno

Masters Theses

"Flexural slip is considered to be an important folding mechanism contributing in the development of different folds such as chevron, and kink-band buckle folds. Various filed studies have provided a general conceptual and qualitative understanding of flexural slip. However, quantitative evidence of the importance of the flexural slip mechanism during fold evolution is sparse, as the actual amount of surface parallel displacement, and timing, is difficult to measure accurately, due to the lack of suitable strain markers.

In this study 2D finite element analysis is used to overcome these disadvantages and to simulate flexural slip during viscoelastic buckle folding. Variations …

Fuzzy Adaptive Resonance Theory: Applications And Extensions, Clayton Parker Smith

Masters Theses

"Adaptive Resonance Theory, ART, is a powerful clustering tool for learning arbitrary patterns in a self-organizing manner. In this research, two papers are presented that examine the extensibility and applications of ART. The first paper examines a means to boost ART performance by assigning each cluster a vigilance value, instead of a single value for the whole ART module. A Particle Swarm Optimization technique is used to search for desirable vigilance values. In the second paper, it is shown how ART, and clustering in general, can be a useful tool in preprocessing time series data. Clustering quantization attempts to meaningfully …

Common Path Pessimism Removal In Static Timing Analysis, Chunyu Wang

Masters Theses

"Static timing analysis is a key process to guarantee timing closure for modern IC designs. However, additional pessimism can significantly increase the difficulty to achieve timing closure. Common path pessimism removal (CPPR) is a prevalent step to achieve accurate timing signoff. To speed up the existing exhaustive exploration on all paths in a design, this thesis introduces a fast multi-threading timing analysis for removing common path pessimism based on block-based static timing analysis. Experimental results show that the proposed method has faster runtime in removing excess pessimism from clock paths."--Abstract, page iii.

Pipeline Leak Detection, Marcia Golmohamadi

Masters Theses

"In the present research two techniques are applied for leak detection in pipelines. The first method is a hardware-based technique which uses ultrasonic wave's emission for pipeline inspection. Ultrasonic waves are propagated in the pipe walls and reflected signal from leakage will be used for pipe analysis. Several Pipes with various dimensions and characteristics are modeled by finite element method using ANSYS. Second order longitudinal modes of ultrasonic waves are emitted in their walls. For this purpose, excited frequency is calculated such that it excites the second order longitude mode. In order to investigate the behavior of emitted wave in …

A Novel Entropy Production Based Full-Chip Tsv Fatigue Analysis, Tianchen Wang

Masters Theses

"Through-silicon vias (TSVs) are subject to thermal fatigue due to stress over time, no matter how small the stress is. Existing works on TSV fatigue all rely on measurement-based parameters to estimate the lifetime, and cannot consider detailed thermal profiles. In this paper, we propose a new method for TSV fatigue prediction using entropy production during thermal cycles. By combining thermodynamics and mechanics laws, the fatigue process can be quantitatively evaluated with detailed thermal profiles. Experimental results show that interestingly, the landing pad possesses the most easy-to-fail region, which generates up to 50% more entropy compared with the TSV body. …

A Sentence-Based Image Search Engine, Weizhi Meng

Masters Theses

"Nowadays people are more interested in searching the relevant images directly through search engines like Google, Yahoo or Bing, these image search engines have dedicated extensive research effort to the problem of keyword-based image retrieval. However, the most widely used keyword-based image search engine Google is reported to have a precision of only 39%. And all of these systems have limitation in creating sentence-based queries for images.

This thesis studies a practical image search scenario, where many people feel annoyed by using only keywords to find images for their ideas of speech or presentation through trial and error. This thesis …

Computer Aided Detection Of Oral Lesions On Ct Images, Shaikat Mahmood Galib

Masters Theses

"Oral lesions are important findings on computed tomography images. They are difficult to detect on CT images because of low contrast, arbitrary orientation of objects, complicated topology and lack of clear lines indicating lesions. In this thesis, a fully automatic method to detect oral lesions from dental CT images is proposed to identify (1) Closed boundary lesions and (2) Bone deformation lesions. Two algorithms were developed to recognize these two types of lesions, which cover most of the lesion types that can be found on CT images. The results were validated using a dataset of 52 patients. Using non training …

Dependability Analysis And Recovery Support For Smart Grids, Isam Abdulmunem Alobaidi

Masters Theses

"The increasing scale and complexity of power grids exacerbate concerns about failure propagation. A single contingency, such as outage of a transmission line due to overload or weather-related damage, can cause cascading failures that manifest as blackouts. One objective of smart grids is to reduce the likelihood of cascading failure through the use of power electronics devices that can prevent, isolate, and mitigate the effects of faults. Given that these devices are themselves prone to failure, we seek to quantify the effects of their use on dependability attributes of smart grid. This thesis articulates analytical methods for analyzing two dependability …

Chemical Quantification With Ubiquitous Optoelectronic Devices, Altamash Mukhtar Fakki

Masters Theses

"Optical sensing in medical diagnosis and chemical analysis using optoelectronic devices is a growing technology since it offers many advantages including real time analysis, remote sensing capability and low cost approach. This thesis demonstrates that an optical sensing platform utilizing optical mouse, the ubiquitous optoelectronic computer peripheral, can be used in quantitative oxygen and pH analysis.

Work in the first paper includes the use of optical mice for fluorescence intensity imaging of commercial oxygen patch. This involves gray color intensity analysis of filtered images to determine the gaseous oxygen level.

In the second paper, the optical mice is used to …

Uterine Cervical Cancer Histology Image Feature Extraction And Classification, Koyel Banerjee

Masters Theses

"The current study presents the investigation and development of image processing, computational intelligence, fuzzy logic, and statistical techniques for different types of data fusion for a varied range of applications. Raw data, decision level and feature level fusion techniques are explored for detection of pre Cervical cancer (CIN) grades from digital histology images of the cervical epithelium tissues.

In previous research, an automated, localized, fusion-based approach was investigated for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on image analysis. The approach included medial axis determination, vertical segment partitioning as medial axis …

Software-Based Instrumentation For Analysis Of Electrostatic Discharge Effects, Antonio James Sabatini

Masters Theses

”Failures caused by electrostatic discharge (ESD) compromise the reliability of embedded systems. Peripherals such as the universal serial bus (USB) are particularly vulnerable, as isolating them to avoid electromagnetic interference would defy their purpose - facilitating communication with and/or by the embedded system. Better understanding the propagation of failures that result from ESD can facilitate defensive development of hardware and software for embedded systems, but is hampered by the lack of non-invasive and lightweight instrumentation techniques.

The original contribution of this thesis is the design and development of software-based instrumentation for monitoring the reaction of the USB peripheral of an …

Quantitative Modeling Of Reliability And Survivability For Cyber-Physical Power Systems, Murtadha Nabeel Albasrawi

Masters Theses

"Critical infrastructure systems are increasingly reliant on cyber infrastructure that enables intelligent real-time control of physical components. This cyber infrastructure utilizes environmental and operational data to provide decision support intended to increase the efficacy and reliability of the system and facilitate mitigation of failure. Realistic imperfections, such as corrupt sensor data, software errors, or failed communication links can cause failure in a functional physical infrastructure, defying the purpose of intelligent control. As such, justifiable reliance on cyber-physical critical infrastructure is contingent on rigorous investigation of the effect of intelligent control, including modeling and simulation of failure propagation within the cyber-physical …

Computer Vision Libraries For Trailer Truck Testbed Using Open Source Computer Vision Libraries, Krishnan Raghavan

Masters Theses

"Computer Vision is a field that aims at understanding and analyzing images from the real world to produce numerical and symbolical data. It is a first step at duplicating the capabilities of human vision by electronically understanding the image and perceiving its features. This work aims at providing some of the features of a human eye to a trailer truck. These features include getting a 3D wireframe from continuous images and prediction of the next position of the objects in view, while the truck is moving.

The thesis has been divided into 3 sections. First section is acquiring images in …