This report describes the study of a new approach to resolve pulse radar range bin ambiguity problem. The nature and the cause of the problem are discussed, and various methods presently used to solve this problem are presented. The report points out the disadvantages of these methods and, thus, introduces a new approach to resolve the radar range bin ambiguity problem by examining the reasonableness of the trajectory of the object being traced. Necessary algorithm and computer programs to support the study are given in Appendices I, II, and III.

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The efficacy of two online instructional methods, guided inquiry and video, were experimentally examined for learning and change of misconceptions regarding learning styles; the relationship of student characteristics to outcomes was also examined. Learners’ mindset interacted with instructional method for learning; additional learner characteristics also indicated some relationship to the efficacy of these instructional methods for learning. Misconceptions, however, were generally resistant to change. Implications for online instruction and future directions for research are explored

Multi Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) is a passive remote sensing technique that has been widely used to derive aerosol extinction coefficient profiles and trace gas concentrations. The ill-posed nature of the MAX-DOAS inversion problem makes it almost impossible to design an inversion algorithm providing a definite solution. A possible way to find a low-error inversion algorithm is incorporating the machine learning (ML) technique into the MAX-DOAS retrieval. This dissertation serves as the author's exploration of designing such an ML-based inversion algorithm. The inversion problem is formulated as a supervised learning problem and the ML models are trained on synthetic datasets simulated by radiative transfer models.newline By starting with a feasibility study, it is first shown that a ML model with appropriate architecture (CNN+LSTM) is capable of extracting aerosol extinction coefficient profile, single scattering albedo and asymmetry factor from one MAX-DOAS scan. Then more realistic atmosphere states were used for generating the training set. Due to the high time cost of radiative transfer simulations, a data augmentation strategy was put forward to increase the number of samples in the training set. A physics-guided machine learning (PGML) algorithm was designed to retrieve aerosol information and trace gas concentrations simultaneously. The model is named as PGML model because: (1) its prediction is based on the physical laws it has learnt from the radiative transfer simulations and (2) introduction of the physical constraints and the pseudo-inverse layer. The PGML model was tested on both a synthetic test set and real MAX-DOAS measurements from Pandora instruments. Evaluation on the synthetic dataset suggests that with similar data distribution, the PGML model is capable of retrieving aerosol extinction coefficient profile, trace gas concentration profile and the box-AMFs with good accuracy. Validation on real data was done via comparisons with inversion results given by other algorithms. Generally, moderate linear correlation were found between the inversion results. Limitation of current version of the PGML model and factors might lead to the discrepancies between inversion results given by the PGML model and other algorithms were discussed. / Doctor of Philosophy / Multi Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) is a passive remote sensing technique for deriving aerosol and trace gas information in the lower atmosphere. A MAX-DOAS instrument is a ground-based system consists of a scanning telescope, a stepping motor and a spectrometer. It collects scattered solar photons at multiple elevation angles. And from spectrum analysis and inversion algorithms, aerosol properties such as aerosol extinction coefficient profile (a vertical profile describing how much the solar radiation is weakened by the atmosphere), single scattering albedo (the ratio of scattered light to incoming light) and trace gas concentrations can be retrieved. The ill-posed nature of the MAX-DOAS inversion problem makes it almost impossible to design an inversion algorithm providing a definite solution. A possible way to find a low-error inversion algorithm is incorporating the machine learning (ML) technique into the MAX-DOAS retrieval. This dissertation serves as the author's exploration of designing such an ML-based inversion algorithm. The inversion problem is formulated as a supervised learning problem. In supervised learning, a training set is used to teach the ML model to yield the desired output. And the ML models are trained on synthetic datasets simulated by radiative transfer models for two reasons: (1) There is no reliable dataset combining real MAX-DOAS measurements and observations of aerosol properties (macrophysical properties and aerosol extinction coefficient profiles) and trace gas concentrations. (2) Most of the existing algorithms somewhat rely on empirical knowledge (e.g.: a priori information (optimal estimation methods), introduction of parameters for representing the state vector (parameterized retrieval algorithms)). However, the method purely relies on the rules it has learned from the training set. By using simulated data, it is expected that the ML model to capture the radiative transfer theory and give predictions based on the physical laws.newline By starting with a feasibility study, it is first shown that by applying a machine learning model with appropriate architecture (combination of convolutional layers and long short-term memory layer), it is possible to extract aerosol extinction coefficient profile, single scattering albedo and asymmetry factor from one MAX-DOAS scan. And this architecture is capable of retrieving elevated layers of aerosol extinction coefficient profiles. Then more realistic atmosphere states were used for generating the training set and designed a physics-guided machine learning (PGML) model to retrieve aerosol information and trace gas concentrations simultaneously. The model is named as PGML model because: (1) its prediction is based on the physical laws it has learnt from the radiative transfer simulations and (2) introduction of the physical constraints and the pseudo-inverse layer. Due to the high time cost of running radiative transfer simulations, a data augmentation strategy was put forward to increase the number of samples in the training set. The PGML model was tested on both a synthetic test set and real MAX-DOAS measurements from Pandora instruments. Evaluation on the synthetic dataset suggests that with similar data distribution, the PGML model is capable of retrieving aerosol extinction coefficient profile, trace gas concentration profile and the box-AMFs with good accuracy. Validation on real data was done via comparisons with inversion results given by other algorithms. Generally, moderate linear correlation were found between the inversion results. Limitation of current version of the PGML model and factors might lead to the discrepancies between inversion results given by the PGML model and other algorithms were discussed.

Teachers encounter numerous challenges within their first years of teaching. More support needs to be provided to assist novice teachers with navigating challenges that have been persistent in the literature on novice teachers. This study considered how engaging in guided reflective inquiry could support novice teachers' abilities to notice and respond to the challenges they encounter. In particular, this study explored the different identities from which novice teachers can draw inspiration to understand how they may support or constrain the process of responding to challenges. Participating in guided reflective inquiry encouraged novice teachers to explore their responses to individual "wobble moments" (Fecho, 2011) and view those uncertainties as moments of growth. The theories of dialogism (Bakhtin, 1981) and dialogical self theory (Hermans and Hermans-Konopka, 2010) provided a lens through which meanings were created from the generated data. This study focused on six novice teachers within their first three years of full-time teaching and implemented elements of transactional analysis (Stewart, 2011) to analyze the narratives, memos, reflections, and interview discussions generated from the participant and researcher. The ways in which novice teachers noticed the challenges they encountered, used the concept of wobble to engage in dialogue with those challenges, and considered how the exploration of one's identity supported or constrained that process were examined in this study. Three generated understandings indexed the importance of enacting approaches to teacher induction that better support novice teachers: (1) challenges encountered by the participants aligned with persistent struggles that have been well-documented in the literature on teacher challenges, (2) participant responses to wobble moments involved a two-step process of an initial reaction and a decided-upon action, and (3) participant developing teacher identities were influenced by numerous aspects of their dialogical self. The implications of this study point to the need to enact approaches to teacher induction that use guided reflective inquiry as an adaptable structure to support novice teachers' abilities to bring their identities into dialogue with the tensions from challenges they experience in their individual teaching contexts. / Doctor of Philosophy / The purpose of this study was to examine ways in which novice teachers can be better supported through the challenges that are often within the first years of teaching. This study employed the theoretical frameworks of dialogism (Bakhtin, 1981) and dialogical self theory (Hermans and Hermans-Konopka, 2010) to consider how engaging in guided reflective inquiry could support a novice teacher's abilities to notice and respond to the challenges encountered. An in-depth exploration of the novice teacher's identity supported the process of examining influences on their responses to challenges. Six teachers participated in this study after meeting the criteria of being employed as an English or Language Arts teacher, teaching students within secondary 6th-12th grades, and being within their first three years of full-time teaching. The study involved three stages: an intake interview, three rounds per participant of submitting a wobble narrative and then discussing the wobble moment via Zoom, and a final reflection and interview. Transactional analysis (Stewart, 2011) assisted in the process of coding and analyzing the data to develop three generated understandings: (1) challenges encountered by the participants aligned with persistent struggles that have been well-documented in the literature on teacher challenges, (2) participant responses to wobble moments involved a two-step process of an initial reaction and a decided-upon action, and (3) participant developing teacher identities were influenced by numerous aspects of their dialogical selves. The implications of the understandings promote the necessity for teacher induction to implement guided reflective inquiry as a way to better support novice teachers through the challenges they encounter.

M. S.

This dissertation presents the exploration of two fiber optics techniques involving high power pulse laser delivery. The first research topic is "Embedded Active Fiber Optic Sensing Network for Structural Health Monitoring in Harsh Environments", which uses the fiber delivered pulse laser for acoustic generation. The second research topic is "Fiber Optics Guided Laser Micromachining", which uses the fiber delivered pulse laser for material ablation. The objective of the first research topic is to develop a first-of-a-kind technology for remote fiber optic generation and detection of acoustic waves for structural health monitoring in harsh environments. Three different acoustic generation mechanisms were studied in detail, including laser induced plasma breakdown (LIB), Erbium-doped fiber laser absorption, and metal laser absorption. By comparing the performance of the acoustic generation units built based on these three mechanisms, the metal laser absorption method was selected to build a complete fiber optic structure health monitoring (FO-SHM) system. Based on the simulation results of elastic wave propagation and fiber Bragg grating acoustic pulse detection, an FO-SHM sensing system was designed and built. This system was first tested on an aluminum piece in the room temperature range and successfully demonstrated its capability of multi-parameter monitoring and multi-point sensing. With additional studies, the upgraded FO-SHM element was successfully demonstrated at high temperatures up to 600oC on P-91 high temperature steels. During the studies of high power pulse laser delivery, it was discovered that with proper laser-to-fiber coupling, the output laser from a multimode fiber can directly ablate materials around the fiber tip. Therefore, it is possible to use a fiber-guided laser beam instead of free space laser beams for micromachining, and this solves the aspect ratio limitation rooted in a traditional laser beam micromachining method. In this dissertation, this Guided Laser MicroMachining (GLMM) concept was developed and experimentally demonstrated by applying it to high aspect ratio micro-drilling. It was achieved that an aspect ratio of 40 on aluminum and an aspect ratio of 100 on PET, with a hole diameter less than 200 um. / PHD / This dissertation presents two research topics both related to high power laser and fiber optic. The first topic studies the application of using optical fiber and high power laser for ultrasonic non-destructive evaluation. The general idea is to use fiber optic to remotely generate and monitor ultrasonic waves on a workpiece. Due to the fact that there are no electronic components involved in the sensing part of the system, this system can work at high temperature and is unsusceptible to EMI. The second topic studies the usage of optical fiber in high aspect ratio micromachining. The key concept is to use a fiber tip and the output high power laser as a "drilling tip", which eliminate the aspect ratio limitation rooted in the traditional free-space laser micromachining method. With this concept and a demonstrative micromachining system, we achieved record-breaking aspect ratio on both aluminum and plastic.

Currently, many missile fire control systems use a three degree of freedom (3-DOF) trajectory model. The three degrees of freedom represent the linear motion of the missile in three dimensions. A 6-DOF model adds roll, pitch, and yaw, or angular motion in three dimensions to the first three degrees of freedom. Because more of the missile’s attributes are modeled, a 6-DOF model is more accurate than a 3-DOF model. For the same reason, a 3-DOF model is easier to develop and executes faster. Also, because a 3-DOF model ignores the seemingly random angular motion, the step sizes used to integrate 3-DOF models are larger. The goal of this project is to develop a 6-DOF re-entry model with the accuracy of a 6-DOF model with conventional equations of motion and computational speed at least comparable to the 3-DOF model. This can be achieved by transforming the equations that compute the effects of angular motion so that they are better conditioned. Essentially, this is done by fitting a sine wave to the oscillating state variables representing the orientation and angular rates, namely the quaternions and the angular velocity. This thesis shows the results of transforming the oscillating variables of the state vector. / Master of Science

The purpose of this research was to determine the feasibility of a laser-based positioning system as a primary navigation method. The system developed for this research consisted of an automated guided vehicle which navigated solely with the use of the laser-based positioning system in real-time. To date, there are no systems which can navigate a pre-defined path using such a positioning system. Some lessons were learned by the researcher, however, concerning the viability of this system in an industrial environment. The system should have had the following advantages over previous systems: 1) Greater range, 2) no prior structuring of environment, 3) real-time navigation, and 4) no reliance on dead-reckoning for navigation. The results showed that goals two through four had been met and are advantages of this system over current systems. The range of this system is limited, however, but it is believed that the next generation system should have greater range than the system used in this research. / Master of Science

A reduced order model describing the energy and heading angle dynamics of a scramjet missile is developed using a singular perturbation technique. The cruise analysis is briefly reviewed to determine the conditions at which the missile will cruise most efficiently. The turn and climb performance of the missile over the conditions of interest is then examined and a family of extremal trajectories is constructed which asymptotically approach the cruise at an intermediate altitude. / Master of Science