This thesis describes the development and the verification of a novel micro probe system for high accurancy downscaled Coordinate Measuring Machines (CMMs).

This thesis consists of 5 chapters. We develop new serial (Chapter 2), parallel (Chapter 3), distributed (Chapter 4) and primal-dual (Chapter 5) stochastic (randomized) coordinate descent methods, analyze their complexity and conduct numerical experiments on synthetic and real data of huge sizes (GBs/TBs of data, millions/billions of variables). In Chapter 2 we develop a randomized coordinate descent method for minimizing the sum of a smooth and a simple nonsmooth separable convex function and prove that it obtains an ε-accurate solution with probability at least 1 - p in at most O((n/ε) log(1/p)) iterations, where n is the number of blocks. This extends recent results of Nesterov [43], which cover the smooth case, to composite minimization, while at the same time improving the complexity by the factor of 4 and removing ε from the logarithmic term. More importantly, in contrast with the aforementioned work in which the author achieves the results by applying the method to a regularized version of the objective function with an unknown scaling factor, we show that this is not necessary, thus achieving first true iteration complexity bounds. For strongly convex functions the method converges linearly. In the smooth case we also allow for arbitrary probability vectors and non-Euclidean norms. Our analysis is also much simpler. In Chapter 3 we show that the randomized coordinate descent method developed in Chapter 2 can be accelerated by parallelization. The speedup, as compared to the serial method, and referring to the number of iterations needed to approximately solve the problem with high probability, is equal to the product of the number of processors and a natural and easily computable measure of separability of the smooth component of the objective function. In the worst case, when no degree of separability is present, there is no speedup; in the best case, when the problem is separable, the speedup is equal to the number of processors. Our analysis also works in the mode when the number of coordinates being updated at each iteration is random, which allows for modeling situations with variable (busy or unreliable) number of processors. We demonstrate numerically that the algorithm is able to solve huge-scale l1-regularized least squares problems with a billion variables. In Chapter 4 we extended coordinate descent into a distributed environment. We initially partition the coordinates (features or examples, based on the problem formulation) and assign each partition to a different node of a cluster. At every iteration, each node picks a random subset of the coordinates from those it owns, independently from the other computers, and in parallel computes and applies updates to the selected coordinates based on a simple closed-form formula. We give bounds on the number of iterations sufficient to approximately solve the problem with high probability, and show how it depends on the data and on the partitioning. We perform numerical experiments with a LASSO instance described by a 3TB matrix. Finally, in Chapter 5, we address the issue of using mini-batches in stochastic optimization of Support Vector Machines (SVMs). We show that the same quantity, the spectral norm of the data, controls the parallelization speedup obtained for both primal stochastic subgradient descent (SGD) and stochastic dual coordinate ascent (SCDA) methods and use it to derive novel variants of mini-batched (parallel) SDCA. Our guarantees for both methods are expressed in terms of the original nonsmooth primal problem based on the hinge-loss. Our results in Chapters 2 and 3 are cast for blocks (groups of coordinates) instead of coordinates, and hence the methods are better described as block coordinate descent methods. While the results in Chapters 4 and 5 are not formulated for blocks, they can be extended to this setting.

Transpacific Investment Corporation –TCI– is a private entity determined to take advantage of the increasing market opportunities arising between Asia and Latin America. TCI is to be incorporated under Guatemalan law in November 2003. The corporation plans to start its operations in Taiwan by February 2004, pioneering into the Spanish Language Industry. The Spanish Language Division of TCI will offer price-competitive opportunities to study Spanish and do tourism in Guatemala. The Division’s tasks will be distributed between two agencies: a Promotion and Recruitment Agency in Taiwan and a Coordination Agency in Guatemala. The latter is in charge of selecting the highly-qualified Spanish Learning Centers and Local Tour Operators that will be responsible for executing the language learning and tourism activities provided to TCI’s clients. Additionally, the Coordination Agency will select adequate insurance and security services to ensure maximum safety for the participants. The promotional efforts will be targeted at university students currently participating in Spanish language courses, and the marketing mix has been designed according to their needs. The leaders of this venture believe that there is a promising opportunity on this field because of the latent popularity of the Latin culture and the price advantages that Guatemala is capable of offering. Currently, more than 1,300 Taiwanese students participate in Spanish language courses. With its diverse products, TCI estimates it can attract at least 33 students on the first year of operations, 49 students on the second year, and 55 students on the third year. These numbers represent, respectively, market shares of 10%, 15%, and 20%, of conservatively defined potential markets. The initial investment required for the venture is slightly above NT 500,000. If the market share goals are achieved, it will be possible to reach the payback period in 13 months, and to enjoy net income above NT 200,000 for the second year, and above NT 800,000 for the third year. These results yield a return-on-investment ratio higher than 1.44.

The all-atom protein backbone reconstruction problem (PBRP) is to reconstruct the 3D coordinates of all atoms, including N, C, and O atoms on the backbone, for a protein whose primary sequence and £\-carbon coordinates are given. A variety of methods for solving PBRP have been proposed, such as Adcock¡¦s method, SABBAC, BBQ, Chang¡¦s and Yen¡¦s methods. In a recent work, Yen et al. found that the results of Chang¡¦s method are not always better than SABBAC. So they apply a tool preference classification to determine which tool is more suitable for predicting the structure of the given protein. In this thesis, we involve BBQ (Backbone Building from Quadrilaterals) and Chang¡¦s method as our candidate prediction tools. In addition, the tool preferences of different atoms (N, C, O) are determined separately. We call the preference classification as an atom classifier, which is built by support vector machine (SVM). According to the preference classification of each atom classifier, a proper prediction tool, either BBQ or Chang¡¦s method, is used to construct the atom of the target protein. Thus, the combination of all atom results, the backbone structure of a protein is reconstructed. The datasets of our experiments are extracted from CASP7, CASP8, and CASP9, which consists of 30, 24, and 55 proteins, respectively. The proteins of the datasets contain only standard amino acids. We improve the average RMSDs of Yen¡¦s results from 0.4019 to 0.3682 in CASP7, from 0.4543 to 0.4202 in CASP8, and from 0.4155 to 0.3601 in CASP9.

An elliptical coordinate transformation was chosen to produce an elliptical cylindrical quantum cloak. Since an ellipse can become to a circle geometrically, research on elliptical quantum cloak provides another way to test the feasibility of the quantum cloak. In this study, it was shown that the effective mass of an elliptical cylindrical quantum cloak is simpler than an circular cylindrical one. Hence, an elliptical quantum cloak is easier to achieve experimentally.

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The purpose of this thesis was to develop the first examples of multifunctional triarylboron-functionalized 8-hydroxyquinoline, their respective aluminum (III) complexes, Al(1)3 and Al(2)3, and diboron analogues, B1 and B2. There was particular focus in investigating the electron accepting characteristics of these systems for potential use as electron transport materials (ETMs) in organic light emitting diodes (OLEDs). The first part of the thesis will discuss the aluminum complexes. Through the introduction of the triarylboron moiety these derivatives of the well-known ETM tris(8-hydroxyquinoline)aluminum (Alq3) exhibited better electron accepting properties than the parent compound. Furthermore, the complexes were able to act as sensors and indicators towards soft Lewis acids such as CN- and hard Lewis acids such as F-, respectively. First the structures of the compounds were investigated using COSY NMR, leading to the discovery that similar to Alq3 the new aluminum complexes possessed the commonly observed mer-isomeric form. Furthermore, their photophysical characteristics were investigated using UV-Vis and fluorescence spectroscopic measurements. The solid state fluorescence quantum yield of Al(1)3 (Φ=0.06) and Al(2)3 (Φ=0.02) were measured and compared to Alq3 (Φ=0.14). In order to better understand these results and gain insight into the electronic transitions of the aluminum complexes, DFT calculations were employed using the B3LYP/6-31G* level of theory. The second part of the thesis will discuss the only examples of diboron-functionalized 8-hydroxyquinoline complexes to date, with one three-coordinate and one four-coordinate boron moiety. Based on CV measurements and DFT calculations, it was discovered that the LUMO of the diboron compounds were lowered substantially compared to their aluminum analogues discussed earlier. More interestingly, it was found that only B1 has any contributions to its LUMO from the triarylboron moiety, leading to the slightly stronger electron accepting ability of B1 compared to B2. Furthermore, these compounds were both able to act as sensors towards small anions such as F-. / Thesis (Master, Chemistry) -- Queen's University, 2011-09-21 08:43:10.543

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Thesis (Ph.D.)--McMaster University, 2004. / Supervisor: Allan D. Spence. Includes bibliographical references (leaves 185-195).

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第18617号 / 情博第541号 / 新制||情||96(附属図書館) / 31517 / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 田中 克己, 教授 吉川 正俊, 教授 黒橋 禎夫 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM