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For several years multi-object spectroscopy systems have been available for carrying out survey work in the visible region, but until very recently there has not been a system for the near infrared region. This thesis describes the design, manufacture and commissioning of the first multi-object fibre system for near infrared spectroscopy. SMIRFS (Spectroscopic Multi-object Infrared Fibre System) is a prototype system that has been designed at the Department of Physics in Durham to couple the Cassegrain focus of the United Kingdom InfraRed Telescope (UKIRT) to a cooled long slit infrared spectrograph (CGS4). Two different fibre bundles are available, each containing 14 fibres. One bundle is made from zirconium fluoride fibres, for K band spectroscopy and the second bundle is made from silica fibres, for J and H band spectroscopy. During the design process of SMIRFS a number of issues were addressed. These included; the characteristics of infrared fibres, in particular their throughput and FRD, atmospheric features in the near infra-red and suitable sky subtraction techniques, fibre preparation and evaluation, the use of microlenses for coupling slow focal ratio beams with fibres, and the thermal emissions from the warm material of the instrument. These, along with the design, manufacture and testing of the SMIRFS are described in detail, including the fibre evaluation results and estimates for throughput, instrument thermal background derived from the commissioning run data. Finally, there is a brief discussion on the development of infrared fibre system for astronomy.

Many things can be communicated through dialogue, including information, thoughts, feelings, attitudes, beliefs and personal experiences. More recently, dialogues have been used in focus group research and in program evaluations. Despite the increasing prevalence of dialogue in research and evaluation, much is still unknown about dialogue, especially how dialogue emerges and occurs within a group setting. The aim of the current study was to describe and identify the various factors involved in a dialogue, examine the relationships among these factors, and conceptualize the process of dialogue within a multi-stakeholder participatory evaluation. A qualitative analysis of three focus groups, each comprised of eight to ten participants, yielded several findings. First, several factors were found to help facilitate the interactions between multiple stakeholders in dialogue, including the development of common ground and specific contributions made by participants. Secondly, communication within these multiple stakeholder groups was found to alternate between two individuals, a dyadic exchange, or between multiple participants, a complex exchange. Thirdly, the moderator and participants were found to take on each other roles. Finally, from these conversations, a model was developed to illustrate the progression of a dialogue in these groups. These results have many implications for program evaluators, focus group leaders, and other practitioners in the field.

This thesis explains and tests a wavelet based implicit numerical method for the solving of partial differential equations. Intended for problems with localized small-scale interactions, the method exploits the form of the wavelet decomposition to divide the implicit system created by the time discretization into multiple, smaller, systems that can be solved sequentially. Included are tests of this method on linear and non-linear problems, with both its results and the time required to calculate them compared to basic models. It was found that the method requires less computational effort than the high resolution control results. Furthermore, the method showed convergence towards high resolution control results.

Many of the undesirable side effects that occur during orthodontic treatment can be attributed directly to a lack of understanding of the physics involved in a given adjustment of an orthodontic appliance. A large number of variables in orthodontic treatment are not within our control, such as growth and tissue response to appliances. However, the force placed on the tooth should be a controllable variable (1), and careful study of the physics underlying our clinical application, can help in reducing those undesirable side effects. If researchers and clinicians can quantify the force systems applied to the teeth, they can better understand clinical and histologic responses. Orthodontic force systems used in everyday orthodontic mechanics are considered indeterminate force systems, in other words, there are too many unknowns to determine the different components of these force systems. Until recently, much of the literature was restricted to experimental two-dimensional analyses of the biomechanical aspects of orthodontic force systems, and computer modeling of three-dimensional analyses. Very little evidence exists in the literature regarding three dimensional experimental measurement and analysis of orthodontic force systems (2). Force system measurements were made on one or two tooth models, however in order for us to understand the orthodontic force systems we need to simultaneously, measure in 3D, the forces being applied on every tooth in the dental arch. With the very recent technological advances in force/torque sensors technology, data acquisition and data representation, it became possible to measure those forces and reveal the force systems we are applying to the dentition. The purpose of this PhD research study is the design and construction of an experimental device that is capable of revealing the details of the force systems used in modern day orthodontic mechano-therapy of continuous arch technique. / Orthodontics

With the proliferation of parallel computing, parallel computer-aided design (CAD) has received significant research interests. Transient transistor-level circuit simulation plays an important role in digital/analog circuit design and verification. Increased VLSI design complexity has made circuit simulation an ever growing bottleneck, making parallel processing an appealing solution for addressing this challenge. In this thesis, we propose and develop a parallel and distributed multi-algorithm approach to leverage the power of multi-core computer clusters for speeding up transistor-level circuit simulation. The targeted multi-algorithm approach provides a natural paradigm for exploiting parallelism for circuit simulation. Parallel circuit simulation is facilitated through the exploration of algorithm diversity where multiple simulation algorithms collaboratively work on a single simulation task. To utilize computer clusters comprising of multi-core processors, each algorithm is executed on a separate node with sufficient system resource such as processing power, memory and I/O bandwidth. We propose two communication schemes, namely master-slave and peer-to-peer schemes, to allow for inter-algorithm communication. Compared with the shared-memory based multi-algorithm implementation, the proposed simulation approach alleviates cache/memory contention as a result of multi-algorithm execution and provides further runtime speedups.

Time series datasets are useful in a wide range of diverse real world applications. Retrieving or querying from a collection of time series is a fundamental task, with a key example being the similarity query. A similarity query returns all time series from the collection that are similar to a given reference time series. This type of query is particularly useful in prediction and forecasting applications. / A key challenge for similarity queries is efficiency and for large datasets, it is important to develop efficient indexing techniques. Existing approaches in this area are mainly based on the Generic Multimedia Indexing Method (GEMINI), which is a framework that uses spatial indexes such as the R-tree to index reduced time series. For processing a similarity query, the index is first used to prune candidate time series using a lower bounding distance. Then, all remaining time series are compared using the original similarity measure, to derive the query result. Performance within this framework depends on the tightness of the lower bounding distance with respect to the similarity measure. Indeed much work has been focused on representation and dimensionality reduction, in order to provide a tighter lower bounding distance. / Existing work, however, has not used employed dimensionality reduction in a flexible way, requiring all time series to be reduced to have the same dimension. In contrast, in this thesis, we investigate the possibility of allowing a variable dimension reduction. To this end, we develop a new and more flexible tree based indexing structure called the Multi-Resolution Index (MR-Index), which allows dimensionality to vary across different levels of the tree. We provide efficient algorithms for querying, building and maintaining this structure. Through an experimental analysis, we show that the MR-Index can deliver improved query efficiency compared to the traditional R-tree index, using both the Euclidean and dynamic time warping similarity measures.

Time series datasets are useful in a wide range of diverse real world applications. Retrieving or querying from a collection of time series is a fundamental task, with a key example being the similarity query. A similarity query returns all time series from the collection that are similar to a given reference time series. This type of query is particularly useful in prediction and forecasting applications. / A key challenge for similarity queries is efficiency and for large datasets, it is important to develop efficient indexing techniques. Existing approaches in this area are mainly based on the Generic Multimedia Indexing Method (GEMINI), which is a framework that uses spatial indexes such as the R-tree to index reduced time series. For processing a similarity query, the index is first used to prune candidate time series using a lower bounding distance. Then, all remaining time series are compared using the original similarity measure, to derive the query result. Performance within this framework depends on the tightness of the lower bounding distance with respect to the similarity measure. Indeed much work has been focused on representation and dimensionality reduction, in order to provide a tighter lower bounding distance. / Existing work, however, has not used employed dimensionality reduction in a flexible way, requiring all time series to be reduced to have the same dimension. In contrast, in this thesis, we investigate the possibility of allowing a variable dimension reduction. To this end, we develop a new and more flexible tree based indexing structure called the Multi-Resolution Index (MR-Index), which allows dimensionality to vary across different levels of the tree. We provide efficient algorithms for querying, building and maintaining this structure. Through an experimental analysis, we show that the MR-Index can deliver improved query efficiency compared to the traditional R-tree index, using both the Euclidean and dynamic time warping similarity measures.

Thesis (M.A.)--Liberty University, 2008. / Includes bibliographical references.

Thesis (M.H.A.)--University of Michigan, 1962.