Beyond its objective basis in natural science, understanding, discussion, and resolution of the policy issue labeled “global warming” also depends on the way it is framed by various groups (Haas, 1992), and ultimately, viewed by members of the general public. Accordingly, there are several prisms, not entirely independent, through which to consider the global warming problem.
Instruction fetch is an important pipeline stage for embedded processors, as it can consume a significant fraction of the total processor energy. This dissertation describes the design and implementation of two new fetch enhancements that seek to improve overall energy efficiency without any performance tradeoff. Instruction packing is a combination architectural/compiler technique that leverages code redundancy to reduce energy consumption, code size, and execution time. Frequently occurring instructions are placed into a small instruction register file (IRF), which requires less energy to access than an L1 instruction cache.
This thesis analyzes the quantitative uncertainty and sensitivity of an intermediate parameter in the OMNIITOX Base Model algorithm which can be used for calculation of characterisation factors to carry out Life cycle assessments (LCA) and Environmental risk assessments (ERA). The quantitative uncertainty of LCA and ERA has been widely recognized, but there exists no estimation of the quantitative uncertainty of the OMNIITOX BM. The purpose of this thesis is to give an example of how large the quantitative uncertainty of an intermediate parameter of OMNIITOX BM can be and which input parameters that contributes the most to this uncertainty. This example could inspire to go further and make a quantitative uncertainty and sensitivity analysis for the complete algorithm, involving all parameters. The methodology that is used in this thesis can be modified to address the issue in more general terms.
The problem of learning a policy, a task representation mapping from world states to actions, lies at the heart of many robotic applications. One approach to acquiring a task policy is learning from demonstration, an interactive technique in which a robot learns a policy based on example state toaction mappings provided by a human teacher.
Because of the enormous earthquake in Sumatra on December 26, 2004, and the devastating tsunami which followed, I have chosen the focus of my mini-course lectures at this year’s PASI to be on two topics which involve the dynamics of surface water waves. These topics are of interest to mathematicians interested in wave propagation, and particularly to Chilean scientists, I believe, because of Chile’s presence on the tectonically active Pacific Rim.
During the past few years, the technique of radiation characterization has undergone a rapid transformation. New materials of construction have made possible a number of improvements in conventional detectors, while several new detector types have been made available to the experimenter. Improvements in detectors have been accompanied by the development of more versatile and reliable electronic measuring equipment. Where once it was possible to record only the number of events in a certain detector, it is now quite common to record complicated spectral data. Many of the new techniques in nuclear data processing were inspired by progress in digital computer technology, which has resulted in a very desirable compatibility between modern nuclear equipment and digital computers. As a result, it now is possible to record and process information from a radiation detection system in a highly automated manner.
In the creation of “surprise tsunami”, submarine landslides head the suspect list. Moreover, improving technologies for seafloor mapping continue to sway perceptions on the number and size of surprises that may lay in wait offshore. At best, an entirely new distribution and magnitude of tsunami hazards has yet to be fully appreciated. At worst, landslides may pose serious tsunami hazard to coastlines worldwide, including those regarded as immune. To raise the proper degree of awareness, without needless alarm, the potential and frequency of landslide tsunami have to be assessed quantitatively. This assessment requires gaining a solid understanding of tsunami generation by landslides, and undertaking a census of the locations and extent of historical and potential submarine slides. This paper begins the process by offering models of landslide tsunami production, propagation and shoaling; and by exercising the theory on several real and hypothetical landslides offshore Hawaii, Norway and the United States eastern seaboard. I finish by broaching a line of attack for the hazard assessment by building on previous work that computed probabilistic tsunami hazard from asteroid impacts.
Leukemia, a heterogeneous group of hematological malignancies, continues to cause significant morbidity and mortality despite decades of research and development. Chromosomal aberrations are the main cause of leukemia and lead to the generation of fusion/chimeric genes, resulting in activation of proto-oncogenes and suppression of tumor-suppressor genes. Incidence of different aberrations associated with different leukemias varies in different regions of the world and the data from population based studies in South Asia, including Pakistan, are lacking.
A quick and stable algorithm for groundwater flow parameter estimation by optimization methods under steady state conditions is presented. A combination of gradient, Gauss-Newton and full Newton algorithms is used. The optimization methods are directly connected with the finite element groundwater flow computations. The sensitivity matrix is computed by a differentiation of the discretized flow equation. The gradient and the complete Hessian are computed by an adjoint state method. By formulating the inverse problem as a maximum likelihood parameter estimation problem, we are able to estimate the parameters as well as quantify the uncertainty associated with the estimates. A two parameter example is used to illustrate the parameter identification procedure. The methodology is applied to a realistic groundwater flow model and MonteCarlo analysis is used to check the results.
The term asbestos is a generic designation referring usually to six types of naturally occurring mineral fibers that are or have been commercially exploited. These fibers belong to two mineral groups: serpentines and amphiboles. The serpentine group contains a single asbestiform variety: chrysotile; five asbestiform varieties of amphiboles are known: anthophyllite asbestos, grunerite asbestos (amosite), riebeckite asbestos (crocidolite), tremolite asbestos, and actinolite asbestos. These fibrous minerals share several properties which qualify them as asbestiform fibers: they are found in bundles of fibers which can be easily separated from the host matrix or cleaved into thinner fibers; the fibers exhibit high tensile strengths, they show high length: diameter (aspect) ratios, from a minimum of 20 up to greater than 1000; they are sufficiently flexible to be spun; and macroscopically, they resemble organic fibers such as cellulose. Since asbestos fibers are all silicates, they exhibit several other common properties, such as incombustibility, thermal stability, resistance to biodegradation, chemical inertia toward most chemicals, and low electrical conductivity.
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