Solving quantum dynamics is an exponentially difficult problem. Thus, an exact numerical solution is inaccessible for any condensed matter system. A promising approach is to divide the system into a quantum subsystem containing degrees of freedom which are of greater interest or those which have more profound quantum character (e.g., have smaller mass) and a classical bath containing the rest of the system. Imposing such a partition and treating the bath classically results in quantum-classical dynamics. The quantum-classical Liouville equation is a general equation in the Hilbert space of quantum degrees of freedom while it resides in the phase space of the classical degrees of freedom. Any numerical solution to this equation requires representation of the quantum subsystem in some basis. Solutions to this equation have been already proposed in the subsystem, adiabatic and force bases, each with its own cons and pros. In this work, the quantum-classical equations of motion are cast in the subsystem basis and subsequently mapped to a number of fictitious harmonic oscillators. The result is quantum-classical dynamics in the mapping basis which treats both quantum and classical degrees of freedom on the same footing, i.e., in phase space. Neglecting a portion of the back reaction of the quantum-subsystem to classical bath results in an expression for the time evolution of an operator (density matrix) equal to its Poisson bracket with the Hamiltonian. This equation can be solved in terms of characteristics to provide a computationally tractable method for calculating quantum-classical dynamical properties. The expressions for expectation values and correlation functions in this formalism are derived. Calculations on spin-boson system, barrier crossing models---the so called Tully models---and the Fenna-Mathews-Olson pigments show very good agreement between the results of this method and numerical solutions to the Schrödinger equation.

Across boreal forests and resource rich areas, human-induced change is rapidly occurring at various spatial scales. In the past, satellite remote sensing has provided a cost effective, reliable method of monitoring these changes over time and over relatively small areas. Those instruments offering high spatial detail, such as Landsat Thematic Mapper or Enhanced Thematic Mapper (TM or ETM+), typically have small swath widths and long repeat times that result in compositing intervals that are too large to resolve accurate time scales for many of these changes. Obtaining multiple scenes and producing maps over very large, forested areas is further restricted by high processing costs and the small window of acquisition opportunity. Coarse spatial resolution instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Very High Resolution Radiometer (AVHRR) typically have short revisit times (days rather than weeks), large swath widths (hundreds of kilometres), and in some cases, hyperspectral resolutions, making them prime candidates for multiple-scale change detection research initiatives. <p>In this thesis, the effectiveness of 250m spatial resolution MODIS data for the purpose of updating existing large-area, 30m spatial resolution Landsat TM land cover map product is tested. A land cover polygon layer was derived by segmentation of Landsat TM data using eCognition 4.0. This polygon layer was used to create a polygon-based MODIS NDVI time series consisting of imagery acquired in 2000, 2001, 2002, 2003, 2004 and 2005. These MODIS images were then differenced to produce six multiple-scale layers of change. Accuracy assessment, based on available GIS data in a subregion of the larger map area, showed an overall accuracy as high as 59% with the largest error associated with change omission (0.51). The Cramers V correlation coefficient (0.38) was calculated using the GIS data. This was compared to the results of an index-based Landsat change detection, Cramers V=0.67. This thesis research showed that areas greater than 15 hectares are adequately represented (approximately 75% accuracy) with the MODIS-based change detection technique. The resulting change information offers potential to identify areas that have been burned or extensively logged, and provides general information on those areas that have experienced greater change and are likely suitable for analysis with higher spatial resolution data.

This study will explore student engagement as a multidimensional construct through a systematic comparative study from the views of students and teachers. While the construct of engagement holds promise for addressing declining motivation and achievement of adolescent students, the challenges associated with measuring a multi-faceted construct suggest the need for integrative research methodologies. This study will utilize concept mapping methods in two urban secondary schools. This methodology holds the potential to provide the tools for structured ‘meaning making’ between participants (students and teachers). This capacity to ‘think together’ is promoted through intentionally structured (i.e., concept mapping processes) practice of discourse. As a direct result of this approach, data revealed the degree of convergence and divergence in student and teacher definitions of student engagement. Areas of student/teacher convergence included themes addressing ‘diversity/belonging’, ‘student-teacher interaction’, and ‘variety in school policy/structure’. Areas of divergence included, ‘aspects of pedagogy’, ‘students at the centre’, and ‘professional educators’. In framing student engagement as a multidimensional construct, this study was able to uncover complex nuances. For example, closer examination of the student data revealed a nested and multi-faceted relationship to their sense of engagement. Students most strongly associated engagement to their sense of belonging at school. In turn, this sense of belonging was directly impacted by their relationships with peers, and this connection was viewed to directly affect on motivation (and subsequent achievement). Future research is needed so as to delve deeper into the nature of social connections among teachers-students, and students-students as an approach to untangle and better understand the multidimensionality of factors at play.

This study will explore student engagement as a multidimensional construct through a systematic comparative study from the views of students and teachers. While the construct of engagement holds promise for addressing declining motivation and achievement of adolescent students, the challenges associated with measuring a multi-faceted construct suggest the need for integrative research methodologies. This study will utilize concept mapping methods in two urban secondary schools. This methodology holds the potential to provide the tools for structured ‘meaning making’ between participants (students and teachers). This capacity to ‘think together’ is promoted through intentionally structured (i.e., concept mapping processes) practice of discourse. As a direct result of this approach, data revealed the degree of convergence and divergence in student and teacher definitions of student engagement. Areas of student/teacher convergence included themes addressing ‘diversity/belonging’, ‘student-teacher interaction’, and ‘variety in school policy/structure’. Areas of divergence included, ‘aspects of pedagogy’, ‘students at the centre’, and ‘professional educators’. In framing student engagement as a multidimensional construct, this study was able to uncover complex nuances. For example, closer examination of the student data revealed a nested and multi-faceted relationship to their sense of engagement. Students most strongly associated engagement to their sense of belonging at school. In turn, this sense of belonging was directly impacted by their relationships with peers, and this connection was viewed to directly affect on motivation (and subsequent achievement). Future research is needed so as to delve deeper into the nature of social connections among teachers-students, and students-students as an approach to untangle and better understand the multidimensionality of factors at play.

Solving quantum dynamics is an exponentially difficult problem. Thus, an exact numerical solution is inaccessible for any condensed matter system. A promising approach is to divide the system into a quantum subsystem containing degrees of freedom which are of greater interest or those which have more profound quantum character (e.g., have smaller mass) and a classical bath containing the rest of the system. Imposing such a partition and treating the bath classically results in quantum-classical dynamics. The quantum-classical Liouville equation is a general equation in the Hilbert space of quantum degrees of freedom while it resides in the phase space of the classical degrees of freedom. Any numerical solution to this equation requires representation of the quantum subsystem in some basis. Solutions to this equation have been already proposed in the subsystem, adiabatic and force bases, each with its own cons and pros. In this work, the quantum-classical equations of motion are cast in the subsystem basis and subsequently mapped to a number of fictitious harmonic oscillators. The result is quantum-classical dynamics in the mapping basis which treats both quantum and classical degrees of freedom on the same footing, i.e., in phase space. Neglecting a portion of the back reaction of the quantum-subsystem to classical bath results in an expression for the time evolution of an operator (density matrix) equal to its Poisson bracket with the Hamiltonian. This equation can be solved in terms of characteristics to provide a computationally tractable method for calculating quantum-classical dynamical properties. The expressions for expectation values and correlation functions in this formalism are derived. Calculations on spin-boson system, barrier crossing models---the so called Tully models---and the Fenna-Mathews-Olson pigments show very good agreement between the results of this method and numerical solutions to the Schrödinger equation.

There are a variety of domains where it is desirable to learn a representation of an environment defined by a stream of sensori-motor experience. This dissertation introduces and formalizes subjective mapping, a novel approach to this problem. A learned representation is subjective if it is constructed almost entirely from the experience stream, minimizing the requirement of additional domain-specific information (which is often not readily obtainable). In many cases the observational data may be too plentiful to be feasibly stored. In these cases, a primary feature of a learned representation is that it be compact---summarizing information in a way that alleviates storage demands. Consequently, the first key insight of the subjective mapping approach is to phrase the problem as a variation of the well-studied problem of dimensionality reduction. The second insight is that knowing the effects of actions is critical to the usefulness of a representation. Therefore enforcing that actions have a consistent and succinct form in the learned representation is also a key requirement. This dissertation presents a new framework, action respecting embedding (ARE), which builds on a recent effective dimensionality reduction algorithm called maximum variance unfolding, in order to solve the newly introduced subjective mapping problem. The resulting learned representations are shown to be useful for reasoning, planning and localization tasks. At the heart of the new algorithm lies a semidefinite program leading to questions about ARE's ability to handle sufficiently large input sizes. The final contribution of this dissertation is to provide a divide-and-conquer algorithm as a first step to addressing this issue.

This thesis is about mapping background radiation in Namibia; specifically in the townships of: Windhoek, Otjiwarongo, Otavi and Tsumeb. No measurements of background radiation in these towns had been carried out before this thesis was done. Even though high levels of background radiation can cause cancer Namibia does not have any laws or recommendations regulating the maximum limits of exposure to background radiation. Our goal was to measure the radiation levels in the four townships mentioned above by using Thermo Luminescent Dosimeters (TLD’s) and carry out instant measurements of background radiation. Then use the results from these measurements to make a map that would be easy for the general public to understand. We have also investigated both the Namibian and the Swedish law to find out if there were any shortcomings in the Namibian law and if it might be possible to use Sweden’s regulations about suitable and appropriate properties in Namibia. The results of the measurements of the background radiation showed that the radiation levels ranged from 0.50 to 2.11 mSv year -1. Compared to the recommended value from the International Conference on Pattern Recognition at 1 mSv year-1the measured values are not exceptionally high. The measurements that were done in this thesis were plotted onto orthophotos of the different townships, thereby creating five maps showing levels of radiation exposure. The levels were colour-coded; green for the lowest, red for highest and yellow and orange for the radiation levels in between. The review of Swedish and Namibian legislation resulted in finding that parts of Sweden’s laws could be applied in Namibia, but some of Namibia’s existing legislation could also be modified to cover radiation exposure. This thesis has concluded that one possible way to mitigate the harmful effects of background radiation and thereby protecting Namibians from acquiring cancer is to expand existing legislation to encompass radiation.

There are a variety of domains where it is desirable to learn a representation of an environment defined by a stream of sensori-motor experience. This dissertation introduces and formalizes subjective mapping, a novel approach to this problem. A learned representation is subjective if it is constructed almost entirely from the experience stream, minimizing the requirement of additional domain-specific information (which is often not readily obtainable). In many cases the observational data may be too plentiful to be feasibly stored. In these cases, a primary feature of a learned representation is that it be compact---summarizing information in a way that alleviates storage demands. Consequently, the first key insight of the subjective mapping approach is to phrase the problem as a variation of the well-studied problem of dimensionality reduction. The second insight is that knowing the effects of actions is critical to the usefulness of a representation. Therefore enforcing that actions have a consistent and succinct form in the learned representation is also a key requirement. This dissertation presents a new framework, action respecting embedding (ARE), which builds on a recent effective dimensionality reduction algorithm called maximum variance unfolding, in order to solve the newly introduced subjective mapping problem. The resulting learned representations are shown to be useful for reasoning, planning and localization tasks. At the heart of the new algorithm lies a semidefinite program leading to questions about ARE's ability to handle sufficiently large input sizes. The final contribution of this dissertation is to provide a divide-and-conquer algorithm as a first step to addressing this issue.

Across boreal forests and resource rich areas, human-induced change is rapidly occurring at various spatial scales. In the past, satellite remote sensing has provided a cost effective, reliable method of monitoring these changes over time and over relatively small areas. Those instruments offering high spatial detail, such as Landsat Thematic Mapper or Enhanced Thematic Mapper (TM or ETM+), typically have small swath widths and long repeat times that result in compositing intervals that are too large to resolve accurate time scales for many of these changes. Obtaining multiple scenes and producing maps over very large, forested areas is further restricted by high processing costs and the small window of acquisition opportunity. Coarse spatial resolution instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Very High Resolution Radiometer (AVHRR) typically have short revisit times (days rather than weeks), large swath widths (hundreds of kilometres), and in some cases, hyperspectral resolutions, making them prime candidates for multiple-scale change detection research initiatives. <p>In this thesis, the effectiveness of 250m spatial resolution MODIS data for the purpose of updating existing large-area, 30m spatial resolution Landsat TM land cover map product is tested. A land cover polygon layer was derived by segmentation of Landsat TM data using eCognition 4.0. This polygon layer was used to create a polygon-based MODIS NDVI time series consisting of imagery acquired in 2000, 2001, 2002, 2003, 2004 and 2005. These MODIS images were then differenced to produce six multiple-scale layers of change. Accuracy assessment, based on available GIS data in a subregion of the larger map area, showed an overall accuracy as high as 59% with the largest error associated with change omission (0.51). The Cramers V correlation coefficient (0.38) was calculated using the GIS data. This was compared to the results of an index-based Landsat change detection, Cramers V=0.67. This thesis research showed that areas greater than 15 hectares are adequately represented (approximately 75% accuracy) with the MODIS-based change detection technique. The resulting change information offers potential to identify areas that have been burned or extensively logged, and provides general information on those areas that have experienced greater change and are likely suitable for analysis with higher spatial resolution data.

The purpose of this study was to investigate the effectiveness of two different concept mapping methods - learner-generated and expert-generated concept mapping - in computer-based video learning. The students’ attitudes toward the use of the concept mapping and computer-based instruction in general were also investigated. The study was performed using the entire enrollment of the junior level undergraduate course (n = 65) Developmental Psychology for Educators (EPSY-320) class, the spring semester of 2010 at Texas A & M University. Using experimental research design, the relationship between student achievements and learning tools was observed. The convenience sampling method was used to assign the students randomly to two treatment groups. The study built on previous research findings on the instructional use of video and concept mapping. It focused on the relative influence of expert-generated versus learner-generated concept maps on student achievement during computer-based video instruction. Results indicated that there were no significant differences among achievements of students who used either learner-generated concept maps or expert-generated concept maps in the study. However, the expert-generated concept mapping group spent significantly less time than the learner-generated concept mapping group interacting with the instructional tool. The findings revealed that concept map scores mediated the relationships between the numbers of clicks on the video player control, time spent creating concept maps, and time spent on all interaction and student achievement. Although the variables - the number of clicks on the video player control, time spent creating concept maps, and time spent on all interactions - did not have a direct effect on student achievement, they affected the concept map scores, which in turn affected student achievement. The three variables - perceived usefulness, ease of use, and attitude toward use - were used to define the attitude of the students toward the instructional tool. The results showed that the attitude of the expert-generated group toward the instructional tool was significantly higher than the learner-generated group. Also, on average, the expert-generated concept mapping group expressed neutral feelings on using the instructional tool to improve their learning performance. Alternatively, the learner-generated group did not appreciate the value of this tool. Both groups reported neutral views about the ease of use of the instructional tool. In conclusion, concept mapping might enhance cognitive learning after the basic skills are acquired and the learners become competent concept mappers. During the creation of concept maps, cognitive load might hinder student learning; therefore, students must be well trained before starting to use the learning tool. Moreover, concept map scores might be used as student grades in video-based learning.