The Multiple Use Plug Hybrid for Nanosats (MUPHyN) prototype thruster incorporates solutions to several major challenges that have traditionally limited the deployment of chemical propulsion systems on small spacecraft. The MUPHyN thruster offers several features that are uniquely suited for small satellite applications. These features include 1) a non-explosive ignition system, 2) non-mechanical thrust vectoring using secondary fluid injection on an aerospike nozzle cooled with the oxidizer flow, 3) a non-toxic, chemically-stable combination of liquid and inert solid propellants, 4) a compact form factor enabled by the direct digital manufacture of the inert solid fuel grain. Hybrid rocket motors provide significant safety and reliability advantages over both solid composite and liquid propulsion systems; however, hybrid motors have found only limited use on operational vehicles due to 1) difficulty in modeling the fuel flow rate 2) poor volumetric efficiency and/or form factor 3) significantly lower fuel flow rates than solid rocket motors 4) difficulty in obtaining high combustion efficiencies. The features of the MUPHyN thruster are designed to offset and/or overcome these shortcomings. The MUPHyN motor design represents a convergence of technologies, including hybrid rocket regression rate modeling, aerospike secondary injection thrust vectoring, multiphase injector modeling, non-pyrotechnic ignition, and nitrous oxide regenerative cooling that address the traditional challenges that limit the use of hybrid rocket motors and aerospike nozzles. This synthesis of technologies is unique to the MUPHyN thruster design and no comparable work has been published in the open literature.

Bibliography: leaves 123-134 / vii, 134 leaves, [20] leaves of plates : ill. (some col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, 1987

We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only pervasive on the nowadays web, but also important to the emerging semantic web. A straightforward approach to automating this process would be to train a classifier for each category in the master taxonomy, and then classify objects from the source taxonomy into these categories. In this paper we attempt to use a powerful classification method, Support Vector Machine (SVM), to attack this problem. Our key insight is that the availability of the source taxonomy data could be helpful to build better classifiers in this scenario, therefore it would be beneficial to do transductive learning rather than inductive learning, i.e., learning to optimize classification performance on a particular set of test examples. Noticing that the categorization of the master and source taxonomies often have some semantic overlap, we propose a new method, Cluster Shrinkage (CS), to further enhance the classification by exploiting such implicit knowledge. Our experiments with real-world web data show substantial improvements in the performance of taxonomy integration. / Singapore-MIT Alliance (SMA)

We compare Naive Bayes and Support Vector Machines on the task of multiclass text classification. Using a variety of approaches to combine the underlying binary classifiers, we find that SVMs substantially outperform Naive Bayes. We present full multiclass results on two well-known text data sets, including the lowest error to date on both data sets. We develop a new indicator of binary performance to show that the SVM's lower multiclass error is a result of its improved binary performance. Furthermore, we demonstrate and explore the surprising result that one-vs-all classification performs favorably compared to other approaches even though it has no error-correcting properties.

Thesis (Ph. D.)--University of Rhode Island, 2005. / Typescript. Includes bibliographical references (leaves 87-89).

Real-time rendering of static volumetric data is generally known to be a memory and computationally intensive process. With the advance of graphic hardware, especially GPU, it is now possible to do this using desktop computers. However, with the evolution of real-time CT and MRI technologies, volumetric rendering is an even bigger challenge. The first one is how to reduce the data transmission between the main memory and the graphic memory. The second one is how to efficiently take advantage of the time redundancy which exists in the time-varying volumetric data. Most previous researches either focus on one problem or the other. In this thesis, we implemented a system which efficiently deals with both of the challenges. We proposed an optimized compression scheme that explores the time redundancy as well as space redundancy of time-varying volumetric data. The compressed data is then transmitted to graphic memory and directly rendered by GPU, so the data transfer between main memory and graphic memory is significantly reduced. With our implemented system, we successfully reduce more than half of the time of transferring the whole data directly. We also compare our proposed compression scheme with the one without exploiting time redundancy. The optimized compression scheme shows a reduce compression distortion over time. With usability, portability and extensibility in mind, the implemented system is also quite flexible.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 69-71).

<p> <p>&nbsp / </p> </p> <p align="left">IP multicast is an efficient mechanism for simultaneously transmitting bulk data to multiple receivers. Many applications can benefit from multicast, such as audio and videoconferencing, multi-player games, multimedia broadcasting, distance education, and data replication. For either technical or policy reasons, IP multicast still has not yet been deployed in today&rsquo / s Internet. Congestion is one of the most important issues impeding the development and deployment of IP multicast and multicast applications.</p>

Since the Euro has founded in 1999, the Asian Currency has become an important issue. The most important prerequisite for adopting common currency for the countries in the area is the synchronization of business cycle. This paper analyses the degree and responses of business cycles for Asian countries when they face to the common shocks. The empirical findings from this paper can be summarized as follows. First, the shocks of Japanese economy are more important to Asian countries than the shocks from the United States, except for Thailand and Indonesia. Second, Malaysia and the Philippine are substantially influenced by the Thailand. Therefore, the Asian economy is evidently forming its regional (or bloc) economy continually. The findings from this paper are in the same line with the result from Hazel (2001), who concludes the business cycles of Japan and Korea are commoved. The degree of synchronization of business cycles for Thailand, Malaysia, and the Philippine are quite high as well.

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