New emission legislations introduced in the European Union and the U.S. have made truck manufacturers face stricter requirements for low emissions and on-board diagnostic systems. The on-board diagnostic system typically consists of several tests that are run when the truck is driving. One way to construct such tests is to use so called consistency relations. A consistency relation is a relation with known variables that in the fault free case always holds. Calculation of a consistency relation typically involves eliminating unknown variables from a set of equations. To eliminate variables from a differential polynomial system, methods from differential algebra can be used. In this thesis, the purely algebraic Gröbner basis algorithm and the differential Rosenfeld-Gröbner algorithm implemented in the Maple package Diffalg have been compared and evaluated. The conclusion drawn is that there are no significant differences between the methods. However, since using Gröbner basis requires differentiations to be made in advance, the recommendation is to use the Rosenfeld-Gröbner algorithm. Further, attempts to calculate consistency relations using the Rosenfeld-Gröbner algorithm have been made to a real application, a model of a Scania diesel engine. These attempts did not yield any successful results. It was only possible to calculate one consistency relation. This can be explained by the high complexity of the model.

This thesis in Educational Sciences consists of a narrative ideology-analysis of the Swedish school's fundamental values with perspectives from the philosophy of Nietzsche and Kant, which also analyzed the same way, with the aim to trace and problematize the ideological foundations of "our society's shared values" that teachers should convey to the students. Based on a theory that a humanism crisis occurs when important values are perceived as threatened, does the introduction of the basic values of the curriculum appear as a response tosocietal changes. Nietzsche and Kant represent completely different idea currents that both have been reflected in the curriculum in which basic values have different meanings. Nietzsche has inspired social criticism, postcolonial and postmodern thinkers to a critical constructivist approach that is an asset in the multicultural classroom to deconstruct stereotypes and prejudices. That culture, ethnicity, morality and religion do not have an objective essence, but seen as social constructions, using a critical approach is a way of thinking which was developed with inspiration from Nietzsche. The school shall strengthen the ability "to live with and realize the values inherent in cultural diversity" is the expression of a postmodern narrative, suggesting that there is not only a valid story, but several. In Nietzsche's perspective, the current standards, such as basic values, is an expression of power, but it is possible to become a superman that frees itself from the prevailing conventions and fulfilling herself, like the postmodern man, or the self-sufficient individual, while Kant rather believe that there are an objective morality that can be reversed by reason that people will follow. Democracy carries the fundamental values of the National Agency for Education. The curriculum values are based on political decision by the Swedish Riksdag and law, but the curriculum refers simultaneously to the ethics borne of humanism. Humanism as Enlightenment, where Kant seems one of the great philosophers of the Enlightenment, is the basis for the curriculum of values. The belief in human rights as a guiding principle and core values constitute a kind of ideology in the curriculum that can be defended by Kant's philosophy, but not with Nietzsche's philosophy. The Curriculum Committee also argues in the report, SOU 1992: 94 for the classic humanistic educational ideal, as both Nietzsche and Kant included, which was weak in Sweden during the post-war period.

Elliptic curve cryptosystem is one type of public-key system, and it can guarantee the same security level with Rivest, Shamir and Adleman (RSA) with a smaller key size. Therefore, the key of elliptic curve cryptography (ECC) can be more compact, and it brings many advantages such as circuit area, memory requirement, power consumption, performance and bandwidth. However, compared to private key system, like Advanced Encryption Standard (AES), ECC is still much more complicated and computationally intensive. In some real applications, people usually combine private-key system with public-key system to achieve high performance. The ultimate goal of this research is to architect a high performance ECC processor for high performance applications such as network server and cellular sites.<p> In this thesis, a high performance processor for ECC over Galois field (GF)(2^163) by using polynomial presentation is proposed for high-performance applications. It has three finite field (FF) reduced instruction set computer (RISC) cores and a main controller to achieve instruction-level parallelism (ILP) with pipeline so that the largely parallelized algorithm for elliptic curve point multiplication (PM) can be well suited on this platform. Instructions for combined FF operation are proposed to decrease clock cycles in the instruction set. The interconnection among three FF cores and the main controller is obtained by analyzing the data dependency in the parallelized algorithm. Five-stage pipeline is employed in this architecture. Finally, the u-code executed on these three FF cores is manually optimized to save clock cycles. The proposed design can reach 185 MHz with 20; 807 slices when implemented on Xilinx XC4VLX80 FPGA device and 263 MHz with 217,904 gates when synthesized with TSMC .18um CMOS technology. The implementation of the proposed architecture can complete one ECC PM in 1428 cycles, and is 1.3 times faster than the current fastest implementation over GF(2^163) reported in literature while consumes only 14:6% less area on the same FPGA device.

Conventional magnetic resonance (MR) imaging has been widely applied to clinical analysis studies due to its non-invasive property. Proton MR spectroscopy complements conventional MR imaging by enabling better lesion characterization. Thus, proton MR spectroscopy is used to assist in the differential diagnosis of intracranial pathologies. LCModel is a reliable and user-friendly post-processing tool which is used to analyse absolute concentrations in our thesis. Our phantom are solution of alanine (Ala), cytosolic amino acids (AAs), lactate (Lac), and n-acetyl aspartate (NAA) in a spherical flasks of glass. We used three basis sets with difference echo time (TE) to experiment. We also performed a retrospective study of subjects with brain abscesses referred during a span of 10 years. All subjects underwent conventional MR imaging and in vivo proton MR spectroscopy, and subjects are classified four groups according to the spectrum characteristics described in the literatures. In this thesis, phantom experiments as well as GAVA simulation are included for the basis sets comparison. Then, abscesses subjects are analyzed by LCModel using these basis sets and compared with clinical diagnosis. Our result shows that using GAVA simulation as the basis sets may provide better consistency among all metabolites and thus achieve more reliable quantification of magnetic resonance spectroscopy.

The objective of the present work is to propose a novel method to extract a stable feature set representative of image content. Each image is represented by a linear combination of fractal orthonormal basis vectors. The mapping coefficients of an image projected onto each orthonormal basis constitute the feature vector. The set of orthonormal basis vectors are generated by utilizing fractal iterative function through target and domain blocks mapping. The distance measure remains consistent, i.e., isometric embedded, between any image pairs before and after the projection onto orthonormal axes. Not only similar images generate points close to each other in the feature space, but also dissimilar ones produce feature points far apart. The above statements are logically equivalent to that distant feature points are guaranteed to map to images with dissimilar contents, while close feature points correspond to similar images. In this paper, we adapt the Multiple Instance Learning paradigm using the Diverse Density algorithm as a way of modeling the ambiguity in images in order to learning concepts used to classify images. A user labels an image as positive if the image contains the concepts, as negative if the image far from the concepts. Each example image is a bag of blocks where only the bag is labeled. The User selects positive and negative image examples to train the concepts in feature space. From a small collection of positive and negative examples, the system learns the concepts using them to retrieve images that contain the concepts from database. Each concept having similar blocks becomes the group in each image. According groups¡¦ location distribution, variation and spatial relations computes positive examples and database images similarity.

Abstract The purpose of this paper is to investigate the impact of foreign capital on the interrelationship between the stock markets and futures markets of Hong Kong, Malaysia and Taiwan. Malaysia stock market is under Exchange Control Mechanism, (ECM) while Taiwan futures market under foreign capital deregulation, both markets has extremely serious influence. The investment behavior of foreign capital, as superior informed investors, always imply their expectation to both stock and futures markets. Thus, this paper attempts to focus on three topics to analyze the investment behavior of the foreign capital. First, whether the degree of intervene of the foreign capital influences the lead-lag relationship. Second, whether after intervene of the foreign capital influence the lead-lag relationship, and third, whether the foreign capital net buying (selling) amount in the stock market influence the basis after deregulation of the Taiwan futures markets. This paper found that under over intervention on futures markets would restrained the stock index futures from price discovered, and after Taiwan futures markets deregulation, foreign capital net buying (selling) amount in the stock market does influence the basis. This study propose both Taiwan stock and futures markets exists foreign capital positive feedback trading.

This thesis presents a preconditioned solenoidal basis method to solve the algebraic system arising from the linearization and discretization of primitive variable formulations of Navier-Stokes equations for incompressible fluid flows. The system is restricted to a discrete divergence-free space which is constructed from the incompressibility constraint. This research work extends an earlier work on the solenoidal basis method for two-dimensional flows and three-dimensional flows that involved the construction of the solenoidal basis P using circulating flows or vortices on a uniform mesh. A localized algebraic scheme for constructing P is detailed using mixed finite elements on an unstructured mesh. A preconditioner which is motivated by the analysis of the reduced system is also presented. Benchmark simulations are conducted to analyze the performance of the proposed approach.

Thesis (M.S.)--University of Hawaii at Manoa, 2005. / Includes bibliographical references (leaves 63-67). Also available via World Wide Web.

Thesis (Ph. D.)--Oregon State University, 2003. / Typescript (photocopy). Includes bibliographical references (leaves 43-46). Also available on the World Wide Web.

The set R of relevant cycles of a graph G is the union of its minimum cycle bases. We introduce a partition of R such that each cycle in a class W can be expressed as a sum of other cycles in W and shorter cycles. It is shown that each minimum cycle basis contains the same number of representatives of a given class W. This result is used to derive upper and lower bounds on the number of distinct minimum cycle bases. Finally, we give a polynomial-time algorithm to compute this partition. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing