3 resultados para Chernoff Distance

em Digital Commons - Michigan Tech


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Reuse distance analysis, the prediction of how many distinct memory addresses will be accessed between two accesses to a given address, has been established as a useful technique in profile-based compiler optimization, but the cost of collecting the memory reuse profile has been prohibitive for some applications. In this report, we propose using the hardware monitoring facilities available in existing CPUs to gather an approximate reuse distance profile. The difficulties associated with this monitoring technique are discussed, most importantly that there is no obvious link between the reuse profile produced by hardware monitoring and the actual reuse behavior. Potential applications which would be made viable by a reliable hardware-based reuse distance analysis are identified.

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During the past decades, tremendous research interests have been attracted to investigate nanoparticles due to their promising catalytic, magnetic, and optical properties. In this thesis, two novel methods of nanoparticle fabrication were introduced and the basic formation mechanisms were studied. Metal nanoparticles and polyurethane nanoparticles were separately fabricated by a short-distance sputter deposition technique and a reactive ion etching process. First, a sputter deposition method with a very short target-substrate distance is found to be able to generate metal nanoparticles on the glass substrate inside a RIE chamber. The distribution and morphology of nanoparticles are affected by the distance, the ion concentration and the process time. Densely-distributed nanoparticles of various compositions are deposited on the substrate surface when the target-substrate distance is smaller than 130mm. It is much less than the atoms’ mean free path, which is the threshold in previous research for nanoparticles’ formation. Island structures are formed when the distance is increased to 510mm, indicating the tendency to form continuous thin film. The trend is different from previously-reported sputtering method for nanoparticle fabrication, where longer distance between the target and the substrate facilitates the formation of nanoparticle. A mechanism based on the seeding effect of the substrate is proposed to interpret the experimental results. Secondly, in polyurethane nanoparticles’ fabrication, a mechanism is put forward based on the microphase separation phenomenon in block copolymer thin film. The synthesized polymers have formed dispersed and continuous phases because of the different properties between segments. With harder mechanical property, the dispersed phase is remained after RIE process while the continuous phase is etched away, leading to the formation of nanoparticles on the substrate. The nanoparticles distribution is found to be affected by the heating effect, the process time and the plasma power. Superhydrophilic property is found on samples with these two types of nanoparticles. The relationship between the nanostructure and the hydrophilicity is studied for further potential applications.

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In this report, we survey results on distance magic graphs and some closely related graphs. A distance magic labeling of a graph G with magic constant k is a bijection l from the vertex set to {1, 2, . . . , n}, such that for every vertex x Σ l(y) = k,y∈NG(x) where NG(x) is the set of vertices of G adjacent to x. If the graph G has a distance magic labeling we say that G is a distance magic graph. In Chapter 1, we explore the background of distance magic graphs by introducing examples of magic squares, magic graphs, and distance magic graphs. In Chapter 2, we begin by examining some basic results on distance magic graphs. We next look at results on different graph structures including regular graphs, multipartite graphs, graph products, join graphs, and splitting graphs. We conclude with other perspectives on distance magic graphs including embedding theorems, the matrix representation of distance magic graphs, lifted magic rectangles, and distance magic constants. In Chapter 3, we study graph labelings that retain the same labels as distance magic labelings, but alter the definition in some other way. These labelings include balanced distance magic labelings, closed distance magic labelings, D-distance magic labelings, and distance antimagic labelings. In Chapter 4, we examine results on neighborhood magic labelings, group distance magic labelings, and group distance antimagic labelings. These graph labelings change the label set, but are otherwise similar to distance magic graphs. In Chapter 5, we examine some applications of distance magic and distance antimagic labeling to the fair scheduling of tournaments. In Chapter 6, we conclude with some open problems.