Computer Engineering Commons^™

Framework For Implementing Advanced Radar Plotting Aid Capability For Small Maritime Vessels, Jason Stark Harris

Electrical & Computer Engineering Theses & Dissertations

Every year in the United States many people are killed or injured when maritime vessels collide with other vessels or fixed objects. According to the United States Coast Guard, the top contributing factors to these collisions are operator inattention, operator inexperience and an improper lookout. Larger commercial vessels are required to have RADAR systems which support Automatic RADAR Plotting Aid (ARPA) which can automatically detect collisions and alert an operator to change course. These systems can be very expensive which put them out of reach of the average recreational boater. It is however possible to implement a low cost ARPA …

Towards A Robust Defense: A Multifaceted Approach To The Detection And Mitigation Of Neural Backdoor Attacks Through Feature Space Exploration And Analysis, Liuwan Zhu

Electrical & Computer Engineering Theses & Dissertations

From voice assistants to self-driving vehicles, machine learning(ML), especially deep learning, revolutionizes the way we work and live, through the wide adoption in a broad range of applications. Unfortunately, this widespread use makes deep learning-based systems a desirable target for cyberattacks, such as generating adversarial examples to fool a deep learning system to make wrong decisions. In particular, many recent studies have revealed that attackers can corrupt the training of a deep learning model, e.g., through data poisoning, or distribute a deep learning model they created with “backdoors” planted, e.g., distributed as part of a software library, so that the …

Applied Deep Learning: Case Studies In Computer Vision And Natural Language Processing, Md Reshad Ul Hoque

Electrical & Computer Engineering Theses & Dissertations

Deep learning has proved to be successful for many computer vision and natural language processing applications. In this dissertation, three studies have been conducted to show the efficacy of deep learning models for computer vision and natural language processing. In the first study, an efficient deep learning model was proposed for seagrass scar detection in multispectral images which produced robust, accurate scars mappings. In the second study, an arithmetic deep learning model was developed to fuse multi-spectral images collected at different times with different resolutions to generate high-resolution images for downstream tasks including change detection, object detection, and land cover …

Electrostatic Design And Characterization Of A 200 Kev Photogun And Wien Spin Rotator, Gabriel G. Palacios Serrano

Electrical & Computer Engineering Theses & Dissertations

High-energy nuclear physics experiments at the Jefferson Lab Continuous Electron Beam Accelerator Facility (CEBAF) require high spin-polarization electron beams produced from strained super-lattice GaAs photocathodes activated to negative electron affinity in a high voltage photogun operating at 130 kV dc. A pair of Wien filter spin rotators in the injector provides precise control of the electron beam polarization at the end station target. An upgrade of the CEBAF injector to better support the upcoming Moller experiment requires increasing the electron beam energy to 200 keV, resulting in better transmission through injector apertures and improved photocathode lifetime. In addition, the energy …

Virtual Satcom, Long Range Broadband Digital Communications, Dennis George Watson

Electrical & Computer Engineering Theses & Dissertations

The current naval strategy is based on a distributed force, networked together with high-speed communications that enable operations as an intelligent, fast maneuvering force. Satellites, the existing network connector, are weak and vulnerable to attack. HF is an alternative, but it does not have the information throughput to meet the distributed warfighting need. The US Navy does not have a solution to reduce dependency on space-based communication systems while providing the warfighter with the required information speed.

Virtual SATCOM is a solution that can match satellite communications (SATCOM) data speed without the vulnerable satellite. It is wireless communication on a …

Deep Cellular Recurrent Neural Architecture For Efficient Multidimensional Time-Series Data Processing, Lasitha S. Vidyaratne

Electrical & Computer Engineering Theses & Dissertations

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in …

Longitudinal Brain Tumor Tracking, Tumor Grading, And Patient Survival Prediction Using Mri, Linmin Pei

Electrical & Computer Engineering Theses & Dissertations

This work aims to develop novel methods for brain tumor classification, longitudinal brain tumor tracking, and patient survival prediction. Consequently, this dissertation proposes three tasks. First, we develop a framework for brain tumor segmentation prediction in longitudinal multimodal magnetic resonance imaging (mMRI) scans, comprising two methods: feature fusion and joint label fusion (JLF). The first method fuses stochastic multi-resolution texture features with tumor cell density features, in order to obtain tumor segmentation predictions in follow-up scans from a baseline pre-operative timepoint. The second method utilizes JLF to combine segmentation labels obtained from (i) the stochastic texture feature-based and Random Forest …

Topology Control, Scheduling, And Spectrum Sensing In 5g Networks, Prosanta Paul

Electrical & Computer Engineering Theses & Dissertations

The proliferation of intelligent wireless devices is remarkable. To address phenomenal traffic growth, a key objective of next-generation wireless networks such as 5G is to provide significantly larger bandwidth. To this end, the millimeter wave (mmWave) band (20 GHz -300 GHz) has been identified as a promising candidate for 5G and WiFi networks to support user data rates of multi-gigabits per second. However, path loss at mmWave is significantly higher than today's cellular bands. Fortunately, this higher path loss can be compensated through the antenna beamforming technique-a transmitter focuses a signal towards a specific direction to achieve high signal gain …

A Multi-Agent Systems Approach For Analysis Of Stepping Stone Attacks, Marco Antonio Gamarra

Electrical & Computer Engineering Theses & Dissertations

Stepping stone attacks are one of the most sophisticated cyber-attacks, in which attackers make a chain of compromised hosts to reach a victim target. In this Dissertation, an analytic model with Multi-Agent systems approach has been proposed to analyze the propagation of stepping stones attacks in dynamic vulnerability graphs. Because the vulnerability configuration in a network is inherently dynamic, in this Dissertation a biased min-consensus technique for dynamic graphs with fixed and switching topology is proposed as a distributed technique to calculate the most vulnerable path for stepping stones attacks in dynamic vulnerability graphs. We use min-plus algebra to analyze …

Coexistence And Secure Communication In Wireless Networks, Saygin Bakşi

Electrical & Computer Engineering Theses & Dissertations

In a wireless system, transmitted electromagnetic waves can propagate in all directions and can be received by other users in the system. The signals received by unintended receivers pose two problems; increased interference causing lower system throughput or successful decoding of the information which removes secrecy of the communication. Radio frequency spectrum is a scarce resource and it is allocated by technologies already in use. As a result, many communication systems use the spectrum opportunistically whenever it is available in cognitive radio setting or use unlicensed bands. Hence, efficient use of spectrum by sharing users is crucial to increase maximize …

Speech Based Machine Learning Models For Emotional State Recognition And Ptsd Detection, Debrup Banerjee

Electrical & Computer Engineering Theses & Dissertations

Recognition of emotional state and diagnosis of trauma related illnesses such as posttraumatic stress disorder (PTSD) using speech signals have been active research topics over the past decade. A typical emotion recognition system consists of three components: speech segmentation, feature extraction and emotion identification. Various speech features have been developed for emotional state recognition which can be divided into three categories, namely, excitation, vocal tract and prosodic. However, the capabilities of different feature categories and advanced machine learning techniques have not been fully explored for emotion recognition and PTSD diagnosis. For PTSD assessment, clinical diagnosis through structured interviews is a …

Deformable Contour Models For Digitizing A Printed Brainstem Atlas, Nirmal J. Patel

Electrical & Computer Engineering Theses & Dissertations

The brainstem is a part of the brain that is connected to the cerebrum and the spinal cord. Ten out of twelve pairs of cranial nerves emerge from the brainstem. The cranial nerves transmit information between the brain and various parts of the body. Due to its anatomical and physiological relevance, a descriptive digital brainstem is important for neurosurgery planning and simulation. For both of these neurosurgical applications, the complexity of the brainstem requires a digital atlas approach to segmentation that maps intensities to tissues rather than less descriptive voxel or surface-based approaches. However, a descriptive brainstem atlas with adequate …

Improving Engagement Assessment By Model Individualization And Deep Learning, Feng Li

Electrical & Computer Engineering Theses & Dissertations

This dissertation studies methods that improve engagement assessment for pilots. The major work addresses two challenging problems involved in the assessment: individual variation among pilots and the lack of labeled data for training assessment models.

Task engagement is usually assessed by analyzing physiological measurements collected from subjects who are performing a task. However, physiological measurements such as Electroencephalography (EEG) vary from subject to subject. An assessment model trained for one subject may not be applicable to other subjects. We proposed a dynamic classifier selection algorithm for model individualization and compared it to other two methods: base line normalization and similarity-based …

Characterization And Decoding Of Speech Representations From The Electrocorticogram, Shreya Chakrabarti

Electrical & Computer Engineering Theses & Dissertations

Millions of people worldwide suffer from various neuromuscular disorders such as amyotrophic lateral sclerosis (ALS), brainstem stroke, muscular dystrophy, cerebral palsy, and others, which adversely affect the neural control of muscles or the muscles themselves. The patients who are the most severely affected lose all voluntary muscle control and are completely locked-in," i.e., they are unable to communicate with the outside world in any manner. In the direction of developing neuro-rehabilitation techniques for these patients, several studies have used brain signals related to mental imagery and attention in order to control an external device, a technology known as a brain-computer …

Idpal – A Partially-Adiabatic Energy-Efficient Logic Family: Theory And Applications To Secure Computing, Mihail T. Cutitaru

Electrical & Computer Engineering Theses & Dissertations

Low-power circuits and issues associated with them have gained a significant amount of attention in recent years due to the boom in portable electronic devices. Historically, low-power operation relied heavily on technology scaling and reduced operating voltage, however this trend has been slowing down recently due to the increased power density on chips. This dissertation introduces a new very-low power partially-adiabatic logic family called Input-Decoupled Partially-Adiabatic Logic (IDPAL) with applications in low-power circuits. Experimental results show that IDPAL reduces energy usage by 79% compared to equivalent CMOS implementations and by 25% when compared to the best adiabatic implementation. Experiments ranging …

Empirical Modeling Of Asynchronous Scalp Recorded And Intracranial Eeg Potentials, Komalpreet Kaur

Electrical & Computer Engineering Theses & Dissertations

A Brain-Computer Interface (BCI) is a system that allows people with severe neuromuscular disorders to communicate and control devices using their brain signals. BCIs based on scalp-recorded electroencephalography (s-EEG) have recently been demonstrated to provide a practical, long-term communication channel to severely disabled users. These BCIs use time-domain s-EEG features based on the P300 event-related potential to convey the user's intent. The performance of s-EEG-based BCIs has generally stagnated in recent years, and high day-to-day performance variability exists for some disabled users. Recently intracranial EEG (i-EEG), which is recorded from the cortical surface or the hippocampus, has been successfully used …

Transparent Spectrum Co-Access In Cognitive Radio Networks, Jonathan Daniel Backens

Electrical & Computer Engineering Theses & Dissertations

The licensed wireless spectrum is currently under-utilized by as much as 85%. Cognitive radio networks have been proposed to employ dynamic spectrum access to share this under-utilized spectrum between licensed primary user transmissions and unlicensed secondary user transmissions. Current secondary user opportunistic spectrum access methods, however, remain limited in their ability to provide enough incentive to convince primary users to share the licensed spectrum, and they rely on primary user absence to guarantee secondary user performance. These challenges are addressed by developing a Dynamic Spectrum Co-Access Architecture (DSCA) that allows secondary user transmissions to co-access transparently and concurrently with primary …

Performance Optimization Over Wireless Links With Operating Constraints, Shiny Abraham

Electrical & Computer Engineering Theses & Dissertations

Wireless communication is one of the most active areas of technological innovations and groundbreaking research ranging from simple cellular phones to highly complex military monitoring devices. The emergence of radios with cognitive capabilities like software defined radios has revolutionized modern communication systems by providing transceivers which can vary their output waveforms as well as their demodulation methods. This adaptability plays a pivotal role in efficient utilization of radio spectrum in an intelligent way while simultaneously not interfering with other radio devices operating on the same frequency band. Thus, it is safe to say that current and future wireless systems and …

Multi-Term Approximation To The Boltzmann Transport Equation For Electron Energy Distribution Functions In Nitrogen, Yue Feng

Electrical & Computer Engineering Theses & Dissertations

Plasma is currently a hot topic and it has many significant applications due to its composition of both positively and negatively charged particles. The energy distribution function is important in plasma science since it characterizes the ability of the plasma to affect chemical reactions, affect physical outcomes, and drive various applications. The Boltzmann Transport Equation is an important kinetic equation that provides an accurate basis for characterizing the distribution function—both in energy and space.

This dissertation research proposes a multi-term approximation to solve the Boltzmann Transport Equation by treating the relaxation process using an expansion of the electron distribution function …

A Vision-Based Automatic Safe Landing-Site Detection System, Yufei Shen

Electrical & Computer Engineering Theses & Dissertations

An automatic safe landing-site detection system is proposed for aircraft emergency landing, based on visible information acquired by aircraft-mounted cameras. Emergency landing is an unplanned event in response to emergency situations. If, as is unfortunately usually the case, there is no airstrip or airfield that can be reached by the un-powered aircraft, a crash landing or ditching has to be carried out. Identifying a safe landing-site is critical to the survival of passengers and crew. Conventionally, the pilot chooses the landing-site visually by looking at the terrain through the cockpit. The success of this vital decision greatly depends on the …

Super-Resolution Of Unmanned Airborne Vehicle Images With Maximum Fidelity Stochastic Restoration, Amr Yousef

Electrical & Computer Engineering Theses & Dissertations

Super-resolution (SR) refers to reconstructing a single high resolution (HR) image from a set of subsampled, blurred and noisy low resolution (LR) images. One may, then, envision a scenario where a set of LR images is acquired with sensors on a moving platform like unmanned airborne vehicles (UAV). Due to the wind, the UAV may encounter altitude change or rotational effects which can distort the acquired as well as the processed images. Also, the visual quality of the SR image is affected by image acquisition degradations, the available number of the LR images and their relative positions. This dissertation seeks …

Smart Sensing And Performance Analysis For Cognitive Radio Networks, Yanxiao Zhao

Electrical & Computer Engineering Theses & Dissertations

Static spectrum access policy has resulted in spectrum scarcity as well as low spectrum utility in today's wireless communications. To utilize the limited spectrum more efficiently, cognitive radio networks have been considered a promising paradigm for future network. Due to the unique features of cognitive radio technology, cognitive radio networks not only raise new challenges, but also bring several fundamental problems back to the focus of researchers. So far, a number of problems in cognitive radio networks have remained unsolved over the past decade. The work presented in this dissertation attempts to fill some of the gaps in the research …

Enhancing Spectrum Utilization In Dynamic Cognitive Radio Systems, Dusadee Treeumnuk

Electrical & Computer Engineering Theses & Dissertations

Cognitive radio (CR) is regarded as a viable solution to enabling flexible use of the frequency spectrum in future generations of wireless systems by allowing unlicensed secondary users (SU) to access licensed spectrum under the specific condition that no harmful interference be caused to the licensed primary users (PU) of the spectrum. In practical scenarios, the knowledge of PU activity is unknown to CRs and radio environments are mostly imperfect due to various issues such as noise uncertainty and multipath fadings. Therefore, important functionalities of CR systems are to efficiently detect availability of radio spectrum as well as to avoid …

Spectrum Adaptation In Cognitive Radio Systems With Operating Constraints, Deepak R. Joshi

Electrical & Computer Engineering Theses & Dissertations

The explosion of high-data-rate-demanding wireless applications such as smart-phones and wireless Internet access devices, together with growth of existing wireless services, are creating a shortage of the scarce Radio Frequency (RF) spectrum. However, several spectrum measurement campaigns revealed that current spectrum usage across time and frequency is inefficient, creating the artificial shortage of the spectrum because of the traditional exclusive "command-and-control" model of using the spectrum. Therefore, a new concept of Cognitive Radio (CR) has been emerging recently in which unlicensed users temporarily borrow spectrum from the licensed Primary Users (PU) based on the Dynamic Spectrum Access (DSA) technique that …

Multi-Scale Edge Detection Algorithms And Their Information-Theoretic Analysis In The Context Of Visual Communication, Bo Jiang

Electrical & Computer Engineering Theses & Dissertations

The unrealistic assumption that noise can be modeled as independent, additive and uniform can lead to problems when edge detection methods are applied to low signal-to-noise ratio (SNR) images. The main reason for this is because the filter scale and the threshold for the gradient are difficult to determine at a regional or local scale when the noise estimate is on a global scale. Therefore, in this dissertation, we attempt to solve these problems by using more than one filter to detect the edges and discarding the global thresholding method in the edge discrimination. The proposed multi-scale edge detection algorithms …

Analysis And Optimization Of Dynamic Spectrum Sharing For Cognitive Radio Networks, Manish Wadhwa

Electrical & Computer Engineering Theses & Dissertations

The goal of this dissertation is to present the analysis and optimization of dynamic spectrum sharing for cognitive radio networks (CRNs). Spectrum scarcity is a well known problem at present. In order to deal with this problem, dynamic spectrum sharing (DSS) was proposed. DSS is a technique where cognitive radio networks dynamically and opportunistically share the channels with primary users. The major contribution of this dissertation is in analyzing the problem of dynamic spectrum sharing under different scenarios and developing optimal solutions for these scenarios. In the first scenario, a contention based dynamic spectrum sharing model is considered and its …

Wavelet-Based Enhancement Technique For Visibility Improvement Of Digital Images, Numan ÜNaldı

Electrical & Computer Engineering Theses & Dissertations

Image enhancement techniques for visibility improvement of color digital images based on wavelet transform domain are investigated in this dissertation research.

In this research, a novel, fast and robust wavelet-based dynamic range compression and local contrast enhancement (WDRC) algorithm to improve the visibility of digital images captured under non-uniform lighting conditions has been developed. A wavelet transform is mainly used for dimensionality reduction such that a dynamic range compression with local contrast enhancement algorithm is applied only to the approximation coefficients which are obtained by low-pass filtering and down-sampling the original intensity image. The normalized approximation coefficients are transformed using …

Tree-D-Seek: A Framework For Retrieving Three-Dimensional Scenes, Saurav Mazumdar

Electrical & Computer Engineering Theses & Dissertations

In this dissertation, a strategy and framework for retrieving 3D scenes is proposed. The strategy is to retrieve 3D scenes based on a unified approach for indexing content from disparate information sources and information levels. The TREE-D-SEEK framework implements the proposed strategy for retrieving 3D scenes and is capable of indexing content from a variety of corpora at distinct information levels. A semantic annotation model for indexing 3D scenes in the TREE-D-SEEK framework is also proposed. The semantic annotation model is based on an ontology for rapid prototyping of 3D virtual worlds.

With ongoing improvements in computer hardware and 3D …

A Subspace Projection Methodology For Nonlinear Manifold Based Face Recognition, Praveen Sankaran

Electrical & Computer Engineering Theses & Dissertations

A novel feature extraction method that utilizes nonlinear mapping from the original data space to the feature space is presented in this dissertation. Feature extraction methods aim to find compact representations of data that are easy to classify. Measurements with similar values are grouped to same category, while those with differing values are deemed to be of separate categories. For most practical systems, the meaningful features of a pattern class lie in a low dimensional nonlinear constraint region (manifold) within the high dimensional data space. A learning algorithm to model this nonlinear region and to project patterns to this feature …

High-Performance Broadcast And Multicast Protocols For Multi-Radio Multi-Channel Wireless Mesh Networks, Jun Wang

Electrical & Computer Engineering Theses & Dissertations

Recently, wireless mesh networks (WMNs) have attracted much attention. A vast amount of unicast, multicast and broadcast protocols has been developed for WMNs or mobile ad hoc networks (MANETs). First of all, broadcast and multicast in wireless networks are fundamentally different from the way in which wired networks function due to the well-known wireless broadcast/multicast advantage. Moreover, most broadcast and multicast protocols in wireless networks assume a single-radio single-channel and single-rate network model, or a generalized physical model, which does not take into account the impact of interference. This dissertation focuses on high-performance broadcast and multicast protocols designed for multi-radio …