Dissertations from the School of Engineering

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Dissertations

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Dissertations from CUA School of Engineering

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: Modeling atmospheric sound propagation in littoral environments; This thesis is focused on atmospheric sound propagation modeling in littoral environments. This work presents the effort of the author toward a numerical model able to predict atmospheric sound propagation in littoral environments. Parabolic equation (PE) acoustic predictions based on measured meteorological data are compared to synchronized acoustic data, when available, to advance the modeling effort. In particular, the effects of wind induced surface roughness, sound absorption due to a sandy beach and wind heterogeneity along the acoustic path are addressed. A method to generate pseudorandom sea profiles consistent with sea wave spectra is presented. How to estimate equivalent effective impedances based on PE predictions with pseudorandom surfaces representing different sea states is discussed. Parametric expressions using acoustic frequency and significant wave height are developed for effective sea surface impedances. Results show coupling between atmospheric refraction and effective impedance. Additionally, the contribution of a sandy beach to atmospheric sound attenuation for a near-shore acoustic source is studied through a case study. Three models of the sandy shore are used to predict the sound pressure level at the water's edge and two range locations beyond the shoreline. Predictions are compared to experimental results. Results show that the sandy beach considered must be modeled as a media with heterogeneous properties along the range to obtain accurate acoustic predictions. Finally, wind heterogeneities along the acoustic range are measured with a LIDAR. Acoustic predictions based on meteorological measurements are compared to acoustic data recorded in littoral and lacustrine environments. Results show that detailed information of temperature and wind profiles is necessary to correctly predict excess attenuation. It was also found that accounting for turbulence in PE prediction is crucial in the case of upward refraction, and leads to better predictions even for downward refraction., Acoustics, atmosphere, littoral environment, meteorology, sea, sound propagation, Mechanical Engineering, Degree Awarded: Ph.D. Mechanical Engineering. The Catholic University of America

: 2D and 3D Computational Optical Imaging Using Deep Convolutional Neural Networks (DCNNs); Traditionally, neural networks (NNs) are used to model a highly complex system architecture that consists of unknown parameters. These parameters can be trained and adapted for unseen inputs to match the correct outputs based on training the system on known matched inputs and outputs. Deep convolutional neural networks (DCNNs), a branch of NNs, offers an encouraging framework providing state-of-the-art performance for many of the image processing problems. In this dissertation, the novel techniques based DCNN are presented that provide the solutions for the inverse problems to compute 2-dimensional phase map distribution and 3-dimensional distribution of refraction index. Instead of using optical complex model-based techniques, the data-driven reconstruction techniques based on machine learning, in particular deep learning (DL), have gained tremendous success in solving complex inverse problems. From that, the reconstruction of 2D phase and 3D refraction index distribution relies on large datasets to ‘learn’ the underlying inverse problem., Electrical engineering, Optics, Computer science, Machine Learning, Microscopy, Quantitative Phase Imaging, Electrical Engineering and Computer Science, Degree Awarded: Ph.D. Electrical Engineering and Computer Science. The Catholic University of America

: 3D Shape, Deformation, Motion and Vibration Measurements using the Stereo-vision-based Techniques; Full-field 3D sensing techniques for shape, deformation, motion, and vibration measurements have emerged as an important tool for numerous applications in various fields. As technologies evolve, there is a high demand to extend the capabilities of the 3D sensing to achieve fast-speed, high-accuracy, and broad-range performance. This dissertation aims to conduct imaging-based research on exploring algorithms and techniques to carry out the 3D shape, deformation, motion and vibration measurements with high accuracy and fast speed. Two stereo-vision-based 3D imaging techniques are investigated: fringe projection profilometry (FPP) and digital image correlation (DIC) techniques. They normally include three key steps: (1) camera calibration, (2) image matching and (3) coordinate determination. Previously, a high-accuracy camera calibration technique based on hyper-precise control-point detection has been developed. Therefore, this dissertation puts emphasis on exploring algorithms related to image matching and 3D coordinate determination as well as the design of the hardware setup. The research work comprises three main components: -Exploration of real-time, high-accuracy 3D imaging and shape measurement techniques using the FPP approach. By encoding three phase-shifted patterns into the red, green, and blue (RGB) channels of a color image and controlling a projector to project the RGB channels individually, the technique can conduct the 3D measurements in real time by synchronizing the projector and the camera. Meanwhile, the measurement accuracy is dramatically improved by introducing novel phase determination schemes.-Exploration of high-accuracy 3D shape, deformation, motion and vibration measurement techniques using the DIC approach. In this work, infrared patterns projected from the Kinect sensor are adopted to considerably facilitate the correlation analysis with enhanced accuracy. Moreover, a technique to acquire 3D digital images of human face without the use of active lighting and artificial patterns is proposed. A few advanced schemes, such as feature-matching-based initial guess, multiple subsets, iterative optimization algorithm, and reliability-guided computation path, are employed.-Incorporation of the deep convolution neural networks (CNNs) concepts into the 3D sensing technique. A single-shot 3D shape reconstruction technique integrating the FPP with the CNNs is proposed. Unlike other complex methods, the novel technique uses an end-to-end network to directly reconstruct a 3D image from its 2D counterpart., Optics, Artificial intelligence, Mechanical engineering, 3D Imaging, Convolutional Neural Networks, Deep learning, Depth estimation, Stereo Vision, Structured light illumination, Mechanical Engineering, Degree Awarded: Ph.D. Mechanical Engineering. The Catholic University of America

: Adaptive Routing Optimization in Continuous-Time Stochastic Dynamic Networks

: Advanced Image Processing in Cardiac Magnetic Resonance Imaging with Application in Myocardial Perfusion Quantification; Cardiac magnetic resonance imaging (CMRI) has been proven to be a valuable source of diagnostic information concerning heart health. One application, myocardial blood flow (MBF) quantification using first-pass contrast-enhanced myocardial perfusion, has aided the detection of coronary artery disease and provides an accurate evaluation of myocardial ischemia, an identifier of coronary artery stenosis. However, the image processing and analysis requires tedious user interaction, increasing the time and effort required to utilize it. In addition, it can introduce subjectivity and variability into the data analysis, which further limits the potential use of the modality. This dissertation presents several automated image processing algorithms to increase the accuracy, consistency, and efficiency of CMR image processing, and validates them on large, clinical datasets.First, an automated method is proposed to measure the arterial input function (AIF) from the left ventricle (LV), which is required for the accurate quantification of MBF. The proposed algorithm consists of several automated image processing steps including motion correction, intensity correction, detection of the LV, independent component analysis, and LV pixel thresholding to calculate the AIF signal. The method was validated in 270 clinical studies by comparing automated results to manual reference measurements using several quality metrics. Additionally, the MBF was calculated and compared in a subset of 21 clinical studies from healthy volunteers using the automated and manual AIF measurements. The proposed method successfully processed 99.63% of the image series. Manual and automatic AIF measurement showed strong agreement, and the automated method effectively selected bright LV pixels, excluded papillary muscles, and required much less processing time than the manual approach. No significant difference was found in MBF estimates between manually and automatically measured AIFs.Second, this dissertation presents an automated method for segmenting the myocardium from MBF maps, making segmental analysis faster and easier to achieve. The proposed method employs active contours for myocardial segmentation, and landmark detection for the anchoring of sector-wise analysis. These methods were validated in a group of 91 clinical perfusion studies against a manual reference standard. The proposed method processed 100% of the studies successfully and results agreed with the manual reference standard, both in terms of segmented area and measurements from sector-wise analysis.Together, these automated methods form a fully automatic MBF quantification pipeline for first-pass contrast-enhanced myocardial perfusion imaging. These advancements make the modality more readily available and applicable to a larger number of patients and centers throughout the field., Computer science, Medical imaging, Cardiac Magnetic Resonance Imaging, Image Processing, Myocardial Perfusion Imaging, Quantification, Segmentation, Electrical Engineering and Computer Science, Degree Awarded: Ph.D. Electrical Engineering and Computer Science. The Catholic University of America

: An Analytical Model and Protocol for Optimizing Quality of Experience in Real-Time Communications; Degree Awarded: Ph.D. Electrical Engineering and Computer Science. The Catholic University of America, This dissertation evaluates the analytical correlations between the quantitative quality of service parameters and qualitative quality of experience; and defines the desired quality of experience and realized quality of experience, to aid in optimizing the quality of experience. Next, this dissertation proposes a cloud-enabled wireless access network architecture that implements software defined networking for control and optimization. And lastly, this dissertation evaluates the benefits of the proposed architecture, utilizing the desired quality of experience. The proliferation of mobile devices and broadband applications has placed tremendous demands on wireless network services. Demands for network accessible multimedia content, especially video, has been growing at a rapid pace. When accessedusing mobile devices via wireless or mobile networks, a high demand is placed on these resource constrained dynamic environments. Optimizing the performance of wireless edge networks to ensure a high quality of experience for all connected users requires employing new capabilities on the edge network. This dissertation introduces the concepts of desired and realized quality of experience, which can be used to normalize the quality that users perceive in order to make more accurate comparisons across a wide range of devices and scenarios.The trend of combining advanced communications and information technologies has created unprecedented opportunities for innovation in network-centric services. The rapid growth in cloud computing and middle box deployment is an outcome of such integration. A similar level of success should be expected if this paradigm is adopted by access networks. This dissertation presents a computation-capable and programmable wireless access network architecture to enable more efficient and robust content delivery.The proposed architecture integrates cloud computing technology to support in-network processing and caching, and software defined networking for flexible management and control of network resources. Finally, this dissertation proposes the framework and algorithms for optimizing the quality of experience of multiple video streams in real-time, subject to wireless transmission capacity and in-network computational power constraints. The framework and algorithms address the multiple resource management challenges that arise in exploiting such integration. The evaluation results show the proposed algorithms significantly improve the average quality of experience of wireless users, especially in congested environments.

: Analytics for Rehabilitative Motion Sensing of Impaired Upper Limbs

: Architecture and Protocol for Optical Packet Switching; Degree awarded: Ph.D. Electrical Engineering and Computer Science. The Catholic University of America, This dissertation proposes a number of single and parallel processor architectures and protocols for optical packet switching in all optical networks making use of a number of recent advances in high speed processors and optical buffers and a number of packet contention resolution techniques in wavelength, time, and space, alternative routing and processing speeds. The input and output lines can transmit multiple wavelengths per line (i.e., wavelength division multiplexed lines). In the developed architectures the header of a packet is separated from the body and is processed for determining the route and wavelength to be used to transmit the packet. The body is delayed for as long as is needed for processing the header. Thus only a portion and not the whole packet need to be saved. This reduces buffer size requirement. The optical packet switch also utilizes dynamically updated Link & Channel Availability Tables and dynamically updated hierarchical Routing Tables (OSPF, Next Best Route). Thirteen different Single Input Processor architectures and the Parallel Input Processor architectures are developed and evaluated with and without packet contention resolution techniques. Parallel processors are used at the output in all architectures except one. The various architectures are simulated by using OPNET software simulation package and their performance is evaluated from these simulation results in terms of packet loss rate, average throughput per line and total throughput. Many of the architectures did not provide acceptable performance. The Parallel Input Processor architecture with the number of wavelength converters equal to the number of input channels and Parallel Input Processor with Next Best Route are shown to provide the best performance (nearly zero packet loss) when using 10 gigabit per second processors for 10 gigabit per second input line rates. Higher rate input lines can be accommodated by down multiplexing the incoming data into 10 gigabit streams and parallel processing these streams. These results are presented on graphical forms. The results of this dissertation will lead to implementation of optical packet switching with its resultant benefits to the all optical networking., Made available in DSpace on 2011-06-24T17:11:38Z (GMT). No. of bitstreams: 1 Condiff_cua_0043A_10223display.pdf: 3336258 bytes, checksum: e441cdbc730441d5059293d456c57350 (MD5)

: Artificial Underwater Electrolocation; Degree awarded: Ph.D. Electrical Engineering and Computer Science. The Catholic University of America, Electric Fields can be used as a means of underwater detection, localization and characterization of objects. Observations of certain species of weakly electric fish suggest the possibility of near-field underwater detection capabilities through the use of biologically inspired electrolocation. A system featuring a dipolar electric field source, analogous to the electric discharge organ of weakly electric fish, and an appropriate arrangement of electric potential sensors could emulate this phenomenon. A mathematical model was developed through the method of images to represent canonical spherical targets in the presence of a static, finite, dipolar electric source in a conducting medium. Characteristics of the electropotential pattern on a sensor array are shown through matrix transform models to predictably vary according to the radius, location and material composition of the target spheres. Transform matrices are determined by parameters relating to a given set of physical circumstances. An inverse model follows from the invertible and linear forward model, such that the relevant target characteristics can be gleaned from a given electropotential pattern and appropriate matrices. The accuracy and effective range of predictions for certain practical cases of varying scales and configurations was calculated by comparing realistic noise and sensor parameters to simulation results. Applications to marine littoral environments were explored as they relate to the simulations., Made available in DSpace on 2011-06-24T17:10:20Z (GMT). No. of bitstreams: 1 Arizzi_cua_0043A_10221display.pdf: 2012937 bytes, checksum: 3fa93563323f4da3b747c3bdaf04bd62 (MD5)

: Authentication and Secure Session Establishment in Body Area Networks Using Multiple Biometrics and Physiological Signals; A body area network (BAN) consists of wireless sensors and actuators attached to orimplanted in a patient’s body for real-time health monitoring and personalized medical care. Itis critical and challenging to secure wireless communications within a BAN in order to protectthe patient’s privacy and also to allow authorized personnel (e.g., doctors and nurses in anemergency room) to easily access and control the BAN without the patient’s involvement oreven when the patient loses consciousness. With the existing key agreement schemes, thedevices are based on a pre-installed secret or a physiological signal feature to authenticateeach other and to agree upon a cryptographic key for secure communications in the BAN. Theformer requires the patient’s involvement to access and configure the BAN, while the latter isnot sufficiently reliable and secure due to signal dynamics. These issues were the motivationfor designing a new key agreement scheme called Multi-Biometric and Physiological Signalbased Key Agreement (MBPSKA) in order to achieve a more secure and reliable authenticationand communication session between BAN devices, while not requiring the patient to providethe secret password. The proposed scheme incorporates reliable biometric traits and timevariant physiological signal features of a patient along with efficient fuzzy crypto-algorithmsand key distribution protocols. The devices use multiple biometric and physiological featuresfor mutual authentication and cryptographic key protection. In order to verify the efficacy ofthe proposed scheme, a number of security characteristics of MBPSKA were assessed, includingrobustness and reliability against various attacks (e.g. replay attack man-in-the-middle attack).The evaluation results using real-world datasets demonstrated that MBPSKA outperforms theexisting physiological signal-based key agreement schemes in terms of security, authenticationreliability, and accuracy. It not only enhances security but also enables flexible and securenetwork access and configuration without the direct involvement of the patient., Computer science, Biometric-based Security, Body Area Network, Key Agreement, Physiological Signal, Secure Communication, Electrical Engineering and Computer Science, Degree Awarded: Ph.D. Electrical Engineering and Computer Science. The Catholic University of America

: Automatic Three-dimensional Reconstruction of Coronal Mass Ejection from STEREO A/B White-light Coronagraph Images; Degree Awarded: Ph.D. Electrical Engineering and Computer Science. The Catholic University of America, Solar activity and its effects on terrestrial and near-terrestrial environments have attained major attention in recent times. Ejections of plasma and magnetic field from the solar atmosphere are capable of disturbing interplanetary medium and producing geomagnetic storms on Earth. The main vehicles of these highly energetic events are the Coronal Mass Ejections (CMEs). One of the missions to observe these solar phenomena is a Solar Terrestrial Relations Observatory (STEREO) Ahead/Behind (A/B) mission. STEREO uses two spacecraft with almost identical instrumentation consisting of a series of coronagraphs (COR) and heliospheric imagers (HI). COR and HI images captured by STEREO A/B spacecraft allow for tracking a CME from two different viewpoints and reconstructing its propagation in a three-dimensional (3D) space. Such 3D reconstruction can be accomplished by using a technique of geometrical triangulation. The geometric triangulation technique, however, requires the location of a CME leading edge in each image to be determined first, followed by an estimation of CME propagation parameters. However, there is currently no robust, reliable, and automatic method to derive CME kinematic properties by tracking a CME leading edge continuously in COR and HI images.To our best knowledge, this dissertation is the first systematic approach to address this issue and to develop a fully automatic pipeline for the CME leading edge tracking and estimation of propagation parameters in COR and HI images. The methods proposed in this dissertation are based on algorithms derived from data analysis with further application of image processing and pattern recognition techniques. The proposed methods include 3 individual modules: one unique approach to segment images in a stack (Pre-processing module) and two different novel approaches to track a CME leading edge and estimate propagation parameters in the stack of segmented images (Tracking modules 1 and 2). Pre-processing module allows for effective background removal and CME segmentation. The output of Pre-processing module is a set of running-difference binary images which can be fed into Tracking module 1 (or 2) to track a CME leading edge and to estimate the propagation parameters. The methods were validated using the selected CME events captured in the period from 1 January 2008 to 31 August 2009. The results demonstrate that the proposed pipeline is effective for CME leading edge tracking and CME propagation parameters estimation. Integration of these innovative approaches with the technique of geometric triangulation will provide a necessary tool for automatic estimation of 3D CME properties.

: Biofabrication of Tissue Constructs Patterned at the Microscale by Hydrogel Deposition and Crosslink Photoprinting; This dissertation aims to introduce and characterize several novel methods of biofabrication, with the overall goal to recapitulate the characteristics and functionality of native tissue. The primary obstacles overcome by these studies are control over biopolymer network density, microstructure, and photocrosslink and molecular patterns on the microscale. The first study describes the creation of dense, aligned collagen networks in microfluidic channels, to aid in the design of tissues on a chip. The second, third and fourth studies describe the printing of photocrosslinks in unmodified biopolymers, to aid in the fabrication of microstructurally and mechanically complex in vitro tissue constructs. The first technique is named microfluidic ionic co-deposition, and it results in tunable collagen microislands with microstructural characteristics similar to the tumor stroma and other connective tissues. This technique has the potential to study cell-mediated remodeling of and drug penetration into dense, aligned tissue constructs. The second technique is two-dimensional photoprinting on a microscope. This approach harnesses visible light and photolithography to generate high-resolution crosslink patterns in hydrogels, visualized through local density alterations in the hydrogel constructs. Importantly, the microscope portion of the instrument provides images of the tissue construct for feedback into potential initial and subsequent photolithography patterns. This technique has potential use for creation of implantable tissue constructs to repair or replace deficient native tissues, or to study cell and tissue behavior in vitro. The findings of this research exhibit both control of biofabricated constructs at the microscale, and the feasibility of influencing cell behavior through photoprinting crosslinks. In the microfluidic approach, collagen microislands were formed and modulated by adjusting microfluidic and biochemical parameters. Similarly, the photobiofabrication method key parameters were determined by printing multiple patterns while varying biopolymer composition, pattern resolution, field size, dot size, illumination intensity and duration. Human fibroblasts were subsequently cultured successfully for over seven days on photoprinted patterns with cell motility and organization depending on the photocrosslink patterns. The findings of this study contribute to the advancement of tissue engineering by providing powerful tools for biofabrication, paving the way for further research and development in this field., Engineering, Biology, Optics, Bio Optics, Biofabrication, Bioprinting, PhotoCrosslinking, Photowriting, Tissue engineering, Biomedical Engineering, Degree Awarded: Ph.D. Biomedical Engineering. The Catholic University of America

: Blockchain-Based Secure Collaboration for Sharing and Accessing Research Data; The rapid development in the online services provides individuals or organizations with the convenience to share data. However, security and privacy are major concerns when data are stored and shared in the cloud. The cloud service system, not the data owner, will directly control data access once the data is uploaded to the cloud. There is a strong need for a platform that allows data owners to not only ensure the security and privacy of their data stored in the cloud, but also to control how to share their own data and track data sharing.One solution is that the data owner encrypts the data before uploading them to the cloud and share the key with authorized users. Attribute-Based Encryption (ABE) is a scheme that provides flexible data encryption and access control based on attribute policies. In particular, with ciphertext-policy attribute-based encryption (CP-ABE), the data owner can encrypt the data with a set of attributes and also includes an access policy. The ciphertext can be decrypted by a recipient if and only if his attributes or credentials satisfy the policy of the ciphertext. However, it is challenging to manage the distribution and revocation of ABE keys as well as prevention of illegal key sharing. On the other hand, blockchain has recently received extensive attentions as a distributed ledger to record, verify, and track transactions. This dissertation aims to design and evaluate a platform for data sharing and collaboration by exploiting attribute-based encryption and blockchain technologies. Hyperledger Fabric is a permission blockchain uses to enable a decentralized and secure data sharing environment and preserves user’s privacy. The proposed platform allows data owners to fully control their data, manage access to the data at a fine-grained level, prevent illegal key sharing and abuse, keep the records of file updates with proof of authorship, and ensure data integrity and privacy. , Computer science, Electrical Engineering and Computer Science, Degree Awarded: Ph.D. Electrical Engineering and Computer Science. The Catholic University of America

: Carbon Nanotube Yarn Monofilament Polymeric Composites: Thermoresistive and Dynamic Piezoresistive Responses; Carbon nanotube yarns (CNTYs) are hierarchical structures built up from thousands of individual carbon nanotubes (CNTs) and their bundles in their cross-section. They exhibit outstanding mechanical, electrical and thermal properties. The coupling between their electrical resistance and temperature (thermoresistivity) and mechanical strain (piezoresistivity) results in an interest for their use in sensing applications. This two-fold study aims to investigate first the thermoresistive response of CNTY/polymer monofilament composites (single CNTY embedded in the polymer) towards the development of in-situ sensors. The second aim is to determine the electrical response of the CNTY/polymer monofilament composites under dynamic loading to determine the working bandwidth and sensitivity of the yarn. Thermoresistive characterization was done to monitor the curing kinetics inside polymeric matrices. This was done by integrating a single CNTY into polymeric matrices with different properties in order to investigate the effect of polymerization kinetics such as resin infiltration, degree of crosslinking, chemical shrinkage, and residual thermal stresses on the electrical response of the embedded yarn. The crosslinked CNTY monofilament composites were subjected to cyclic and incremental-dwell temperature programs and their thermoresistive response was systematically studied. A reference strain gauge was used to calibrate the response of the CNTY and obtain the sensitivity of the CNTY monofilament composite over a range of frequencies and amplitudes. A frequency response function (FRF) was determined between the fractional change in resistance and base acceleration to analyze the bandwidth of the CNTY monofilament composites. Another FRF was simultaneously measured between the output strain and base acceleration in order to obtain the dynamic piezoresistive sensitivity, which is defined as the fractional change in resistance versus strain. The knowledge unveiled in this study will provide the fundamentals to develop integrated thermistors and sensors that could monitor dynamic signals., Mechanical engineering, Materials Science, Polymer chemistry, Carbon nanotube yarns, Carbon nanotubes, Piezoresistivity, Smart Structures, Thermal Characterization, Thermoresisitivity, Mechanical Engineering, Degree Awarded: Ph.D. Mechanical Engineering. The Catholic University of America

: Carbon Nanotube Yarns: Tailoring Their Piezoresistive Response Towards Sensing Applications

: Characterization of the Acoustic Field in Marine Environments with Anthropogenic Noise; Most animals inhabit the aquatic environment are acoustical-oriented, due to the physical characteristics of water that favors sound transmission. Many aquatic animals depend on underwater sound to navigate, communicate, find prey, and avoid predators. The degradation of underwater acoustic environment due to human activities is expected to affected these animals' well-being and survival at the population level. This dissertation presents three original studies on the characteristics and behavior of underwater sound fields in three unique marine environments with anthropogenic noises.The first study examines the soundscape of the Chinese white dolphin habitat in Taiwan. Acoustic recordings were made at two coastal shallow water locations, Yunlin and Waisanding, in 2012. Results show that croaker choruses are dominant sound sources in the 1.2-2.4 kHz frequency band for both locations at night, and noises from container ships in the 150-300 Hz frequency band define the relative higher broadband sound levels at Yunlin. Results also illustrate interrelationships among different biotic, abiotic, and anthropogenic elements that shape the fine-scale soundscape in a coastal environment.The second study investigates the inter-pulse sound field during an open-water seismic survey in coastal shallow waters of the Arctic. The research uses continuous acoustic recordings collected from one bottom-mounted hydrophone deployed in the Beaufort Sea in summer 2012. Two quantitative methods were developed to examine the inter-pulse sound field characteristics and its dependence on source distances. Results show that inter-pulse sound field could raise the ambient noise floor by as much as 9 dB, depending on ambient condition and source distance.The third study examines the inter-ping sound field of simulated mid-frequency active sonar in deep waters off southern California in 2013 and 2014. The study used drifting acoustic recorder buoys to collect acoustic data during sonar playbacks. The results show strong band-limited elevation (13-24 dB) of sound pressure levels for over half of the inter-ping intervals above the natural background levels.These three studies provide insights on the dynamics of marine soundscape and how anthropogenic activities can change the acoustic habitat by elevating the overall sound field levels., Degree awarded: Ph.D. Mechanical Engineering. The Catholic University of America

: Characterization of the Atmosphere as a Random Bit-Stream Generator in a Weak Turbulence Regime; The purpose of this dissertation is to investigate the extent to which atmospheric turbulence can be exploited as a robust random number generator. Atmospheric turbulence is considered an inherently random process, due to the complex non-homogeneous system composition and its sensitivity to changes in pressure, temperature, humidity, wind speed and direction. This work describes the background theory on atmospheric turbulence, which attempts to describe its dynamic behavior, as well as experimental work. A Mach-Zehnder interferometer was designed, built, and used to characterize the work in this dissertation; this sensor system enables the collection of empirical data of the phase fluctuation in the temporal domain introduced to an optical beam propagating through the atmosphere. The recorded phase fluctuations were converted into bit streams that were further analyzed in order to search for evidence of non-random properties. Empirical data and results, which attempt to characterize the degree of randomness in the noise introduced into the temporal phase component of an optical wave propagating through the atmosphere as a function of the atmospheric turbulence in the weak turbulence regime, are presented here for the first time., Degree awarded: Ph.D. Electrical Engineering and Computer Science. The Catholic University of America

: Classification of Cancer Cells Using Digital Holographic Microscopy and Machine Learning to Predict Disease-Relevant Behavior

: Coherent Frequency-Modulated Continuous Wave Ladar Using a Distributed Feedback Laser Array; Optical frequency-modulated continuous-wave (FMCW) reflectometry is a ranging technique that allows for high-resolution distance measurements over long ranges. Similarly, swept-source optical coherence tomography (SS-OCT) provides high-resolution depth imaging over typically shorter distances and higher scan speeds. In this dissertation, a novel, low-cost, low-bandwidth ranging and imaging system is presented that provides the high axial resolution normally associated with SS-OCT over meters of depth. The imaging system combines 12 distributed feedback laser (DFB) elements from a single butterfly module to provide an axial resolution of 27 microns. Active sweep linearization is used, greatly reducing the signal processing overhead. A laser phase noise model is derived to provide insight into the measurement accuracy. Various sub-surface, OCT-style tomograms of semi-transparent objects are shown, as well as 3-D maps of various objects over depths ranging from sub-millimeter to several meters. Such imaging capability would make long-distance, high-resolution surface interrogation possible in a low-cost, compact package., Electrical engineering, Optics, FMCW, lidar, Electrical Engineering and Computer Science, Degree Awarded: Ph.D. Electrical Engineering and Computer Science. The Catholic University of America

: A Comparative Study of Reported and Perceived Driving Behavior in Relation to Road Crashes in Three Different Regions of the Kingdom of Saudi Arabia; Road traffic safety represents the procedures implemented and actualized to inhibit drivers and operators from being killed or significantly wounded. Traffic safety is vital to the enhancement and preservation of economic, social, and environmental aspects of any society. In the Kingdom of Saudi Arabia, road traffic crashes have become to be a very severe issue and the country has already taken steps in resolving this issue. However, previously conducted scientific studies regarding road safety in the KSA were limited to a certain age group.In this dissertation, road traffic crashes were studied in three regions of the KSA (Makkah, Riyadh, and Dammam) based on: driving behavior, locus of control, demographic factors, time of the day, type of road. In addition questionnaire was used to assess driving behavior. Different statistical models such as the random parameters Poisson regression, MANOVA, and logistic binary regression were used to conduct the investigation. The results of the study indicate the following, aggressive behavior increases the chances of both getting into a car crash and being injured in one. Therefore, the KSA should introduce measures in order to control and train drivers who tend to driveaggressively. Furthermore, the programs should include and be adjusted to different demographic groups. The results indicated that the period between 12 am and 6 am is the time of the day when the chances for a road crash are the highest. The dissertation also adapted the DBQ for use in the KSA, and demonstrated its validity by cross-matching the responses on the questionnaire with official reports. This questionnaire could be a useful tool for selecting people to attend road safety programs. This dissertation is a very valuable source of information for the KSA as well as a base for future research., Civil engineering, Transportation, Crashes, Driving Behavior, Poisson, Random Parameters, Civil Engineering, Degree Awarded: D.Engr. Civil Engineering. The Catholic University of America