Thesis (Ph. D.)--University of Wisconsin, 1964. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (p. 78-81).

In common with other countries India has been drawn into a global trend of standardising national accounting practices with international norms to enhance its ability to attract inward foreign investment and gain increased access to global capital markets. In 2004, India committed itself to achieving convergence with International Public Sector Accounting Standards (IPSAS) in the public sector and in 2007 to International Financial Reporting Standards (IFRS) in the private sector. Both sectors have taken the route to convergence with clear cut roadmaps being designed by the national accounting standard setters and the state. However, there has been a striking contrast in the decision-making processes and preparations for convergence in the two sectors. While the public sector made relatively good progress in terms of following the scheduled roadmap, the first roadmap issued for the private sector was scrapped, new deadlines were set and the roadmap was replaced in 2013 due to severe delays in the process which as of August 2016 have not yet been fully resolved. This cross-sector comparison is interesting because the contrasting decision-making scenarios in India exist despite the state being the central decision-maker in both sectors. Hence, while much existing literature on standardisation takes the decision to converge as a given and focuses on the implementation of IFRS or IPSAS, the purpose of this thesis is to examine the processes that led to the convergence decisions. Using a transnational governance theoretical lens, this thesis investigates the chaotic routes through which the idea of convergence travels before being finalised as an implementation decision, in both the public and private sectors in India. The research questions focus on unravelling the development of the convergence decision-making process in India, tracing the networks of national and transnational actors driving the process, analysing the two-way interactive dynamics between actors that shaped the process and examining the role of the state as the central decision-maker in the public and private sectors. The research methods included documentary analysis and in-depth interviews with key individuals in India, with substantial knowledge about the decision making with regards to convergence. Key empirical findings are as follows. Firstly, while in the early phases of decision-making, transnational influences, in the form of international financial institutions and standard setting agencies, were equally apparent in both sectors, in subsequent phases the transnational influences were greater and arguably more successful in the public than the private sector. Secondly, local resistance formed and was successful in delaying the project of IFRS convergence in the private sector. Local actors were successful in raising their concerns about, for example, fair value accounting and the impacts of IFRS accounting on taxation, and in the context of a turbulent political environment, their influence was powerful enough to cause delays. Thirdly, the empirics show the significance of foreign governments and inter-governmental regional networks as an important source of influence on the decision to delay IFRS convergence. Specifically, the study demonstrates how India’s position was also affected by the decision of the US, a major trading partner, to delay its convergence with IFRS, and by the informal links with countries such as Japan, another significant economic counterpart. This thesis has three important areas of contributions. Firstly, it makes a significant methodological contribution by studying convergence as a process rather than an event by tracing the dynamics preceding the actual implementation of international accounting standards. Conducting a study in such a manner entails identifying the multiplicity of actors involved in the convergence project, their concerns and opinions with regards to convergence, the means through which they voice these concerns, and the ultimate drivers of the decision-making behind convergence. Therefore, this study draws attention to the significance of understanding and fully accounting for the pre-implementation phase of convergence as such an understanding has a potential to provide a deeper insight into the primary sources of the difficulties with standards implementation observed in many countries. Secondly, this thesis contributes substantially to the existing standardisation literature. In most prior studies the discussion on accounting standardisation broadly revolves around the advantages and disadvantages of convergence, drivers of convergence and issues of compliance with international accounting standards. While this study finds the significant presence of transnational actors, a deeper analysis into the reasons for convergence delays in India was traced to a variety of legislative, political and economic concerns of stakeholders, especially local actors including potential users of these standards. Thirdly, this study contributes to the literature on global governance by highlighting the importance of not losing sight of the nation state as an important player in the transnational governance arena. Specifically, literature on global (accounting) regulation devotes a great deal of attention to the roles of organisations and agencies with transnational remits (such as global standard setters and donor agencies) while often downplaying the significant impacts of the more traditional cross-country links forged through economic relationships and resource dependencies. The aforementioned influences of India’s links with countries such as US and Japan on the decision-making process as well as India’s regional alliances with neighbouring Malaysia and China provide a vivid indication of the important roles of cross-governmental relationships in the global governance arena and also questions the position of transnational organizations as pervasive powers in such governance. The study’s findings clearly demonstrate that the pursuit of full IFRS convergence strongly favoured by the transnational forces was invariably challenged in the Indian context by the influences of powerful nation states advocating a more cautious approach.

Cette thèse contient des preuves de convergence ou de divergence d'algorithmes d'optimisation appelés stratégies d'évolution (ESs), ainsi que le développement d'outils mathématiques permettant ces preuves.Les ESs sont des algorithmes d'optimisation stochastiques dits ``boîte noire'', i.e. où les informations sur la fonction optimisée se réduisent aux valeurs qu'elle associe à des points. En particulier, le gradient de la fonction est inconnu. Des preuves de convergence ou de divergence de ces algorithmes peuvent être obtenues via l'analyse de chaînes de Markov sous-jacentes à ces algorithmes. Les preuves de convergence et de divergence obtenues dans cette thèse permettent d'établir le comportement asymptotique des ESs dans le cadre de l'optimisation d'une fonction linéaire avec ou sans contrainte, qui est un cas clé pour des preuves de convergence d'ESs sur de larges classes de fonctions.Cette thèse présente tout d'abord une introduction aux chaînes de Markov puis un état de l'art sur les ESs et leur contexte parmi les algorithmes d'optimisation continue boîte noire, ainsi que les liens établis entre ESs et chaînes de Markov. Les contributions de cette thèse sont ensuite présentées:o Premièrement des outils mathématiques généraux applicables dans d'autres problèmes sont développés. L'utilisation de ces outils permet d'établir aisément certaines propriétés (à savoir l'irreducibilité, l'apériodicité et le fait que les compacts sont des small sets pour la chaîne de Markov) sur les chaînes de Markov étudiées. Sans ces outils, établir ces propriétés était un processus ad hoc et technique, pouvant se montrer très difficile.o Ensuite différents ESs sont analysés dans différents problèmes. Un (1,\lambda)-ES utilisant cumulative step-size adaptation est étudié dans le cadre de l'optimisation d'une fonction linéaire. Il est démontré que pour \lambda > 2 l'algorithme diverge log-linéairement, optimisant la fonction avec succès. La vitesse de divergence de l'algorithme est donnée explicitement, ce qui peut être utilisé pour calculer une valeur optimale pour \lambda dans le cadre de la fonction linéaire. De plus, la variance du step-size de l'algorithme est calculée, ce qui permet de déduire une condition sur l'adaptation du paramètre de cumulation avec la dimension du problème afin d'obtenir une stabilité de l'algorithme. Ensuite, un (1,\lambda)-ES avec un step-size constant et un (1,\lambda)-ES avec cumulative step-size adaptation sont étudiés dans le cadre de l'optimisation d'une fonction linéaire avec une contrainte linéaire. Avec un step-size constant, l'algorithme résout le problème en divergeant lentement. Sous quelques conditions simples, ce résultat tient aussi lorsque l'algorithme utilise des distributions non Gaussiennes pour générer de nouvelles solutions. En adaptant le step-size avec cumulative step-size adaptation, le succès de l'algorithme dépend de l'angle entre les gradients de la contrainte et de la fonction optimisée. Si celui ci est trop faible, l'algorithme convergence prématurément. Autrement, celui ci diverge log-linéairement.Enfin, les résultats sont résumés, discutés, et des perspectives sur des travaux futurs sont présentées. / In this dissertation an analysis of Evolution Strategies (ESs) using the theory of Markov chains is conducted. Proofs of divergence or convergence of these algorithms are obtained, and tools to achieve such proofs are developed.ESs are so called "black-box" stochastic optimization algorithms, i.e. information on the function to be optimized are limited to the values it associates to points. In particular, gradients are unavailable. Proofs of convergence or divergence of these algorithms can be obtained through the analysis of Markov chains underlying these algorithms. The proofs of log-linear convergence and of divergence obtained in this thesis in the context of a linear function with or without constraint are essential components for the proofs of convergence of ESs on wide classes of functions.This dissertation first gives an introduction to Markov chain theory, then a state of the art on ESs and on black-box continuous optimization, and present already established links between ESs and Markov chains.The contributions of this thesis are then presented:o General mathematical tools that can be applied to a wider range of problems are developed. These tools allow to easily prove specific Markov chain properties (irreducibility, aperiodicity and the fact that compact sets are small sets for the Markov chain) on the Markov chains studied. Obtaining these properties without these tools is a ad hoc, tedious and technical process, that can be of very high difficulty.o Then different ESs are analyzed on different problems. We study a (1,\lambda)-ES using cumulative step-size adaptation on a linear function and prove the log-linear divergence of the step-size; we also study the variation of the logarithm of the step-size, from which we establish a necessary condition for the stability of the algorithm with respect to the dimension of the search space. Then we study an ES with constant step-size and with cumulative step-size adaptation on a linear function with a linear constraint, using resampling to handle unfeasible solutions. We prove that with constant step-size the algorithm diverges, while with cumulative step-size adaptation, depending on parameters of the problem and of the ES, the algorithm converges or diverges log-linearly. We then investigate the dependence of the convergence or divergence rate of the algorithm with parameters of the problem and of the ES. Finally we study an ES with a sampling distribution that can be non-Gaussian and with constant step-size on a linear function with a linear constraint. We give sufficient conditions on the sampling distribution for the algorithm to diverge. We also show that different covariance matrices for the sampling distribution correspond to a change of norm of the search space, and that this implies that adapting the covariance matrix of the sampling distribution may allow an ES with cumulative step-size adaptation to successfully diverge on a linear function with any linear constraint.Finally, these results are summed-up, discussed, and perspectives for future work are explored.

Prediction markets have recently gained favour with the academic and business communities. Prediction markets have evolved a long way from their basic beginnings as friendly wagers among friends to become large scale markets connecting traders from around the world. They have been adopted into many large and dynamic corporations that require up to the minute information that can keep up with their business. Organisations like Google, HP, Yahoo! and Best Buy have been experimenting with prediction markets for demand forecasting tasks. Governments have also been using markets, although not always as successfully. The U.S. government looked at PAM which became the terrorist futures market in the post 9/11 world. This did not appeal to the American populous and it has since been withdrawn. Through technological advancements the capabilities and availability of prediction markets has grown. With this the interest in how they work and what can be done to improve the accuracy of the markets. This research looked at the inclusion of a deliberative technique to the markets to improve that accuracy of the market. For this research, markets that made use of discussion boards were used. They were compared against traditional markets, which had no means of communication between traders.The research took the form of a quantitative comparison between the two market types. Data was acquired from the Iowa Electronics Market (IEM) and Inkling Public Markets. The findings from this research indicate that there was a significant difference with α=0.012 for the markets at close. This indicated that there was a significant between the traditional (control) and non-traditional (experimental groups) markets from descriptive statistics it was indicated that the traditional markets performed better in the prediction tasks. The conclusions of this research indicate that allowing traders to communicate and see the actions of others creates group biases which impacts on their independence when making trades and thus on the performance of the market.Copyright / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

Using a pseudo-bisymmetric enriched cl-premonoid as the underlying lattice, we examine different categories of lattice-valued spaces. Lattice-valued topological spaces, uniform spaces and limit spaces are described, and we produce a new definition of stratified lattice-valued uniform convergence spaces in this generalised lattice context. We show that the category of stratified L-uniform convergence spaces is topological, and that the forgetful functor preserves initial constructions for the underlying stratified L-limit space. For the case of L a complete Heyting algebra, it is shown that the category of stratified L-uniform convergence spaces is cartesian closed.

La présence de cavités souterraines génère un risque pour les populations et a un impact sur le futur usage des terrains sous-cavés. En combinant observations in situ et analyse des matériaux en laboratoire, cette étude propose de cerner les processus responsables de la dégradation des vides souterrains, sur l’exemple des carrières souterraines de craie autour de Lille.De nombreux désordres (remontées de voûte, ruptures de piliers, effondrements des blocs rocheux) ont été observés lors de la visite de 10 carrières. L’analyse structurale de la craie montre la présence de nombreuses fracturations notamment les diaclases qui se présentent parfois sous forme des couloirs fracturés. L’état de la stabilité des carrières observé sur le terrain a été confirmé par le traitement des données des cannes de convergences entre le ciel et le mur de plusieurs carrières souterraines. Les résultats de ces analyses ont montré que la vitesse des déformations des épontes est d’une manière générale très faible. Le recensement des incidents sur une vingtaine d’années a montré une corrélation entre les épisodes de fortes pluies et les désordres en surface. Les processus d'altération de la craie in situ et les interactions avec l'eau se traduisent par la formation de patines différentes en surface de la craie. Les observations microscopiques ont révélé des modifications des caractéristiques de la surface de la craie, notamment des phénomènes de précipitation de calcite, le dépôt d’oxy-hydroxydes de fer et la modification de la porosité. / The presence of underground cavities creates a potential hazard for population and has a direct impact on land values. Combining observations and analyses of materials in laboratory, the present research work focuses on the phenomena of underground cavity degradation on site and in laboratory, on the example of the Lille Metropole chalk underground quarries. Many disorders (collapse by roof rupture, breakdown of pillars, collapse of the rock blocks) were observed during 10 site visits. The structural analysis of the chalk shows the presence of many fractures, especially joints which sometimes concentrate along corridors. The steady state of quarries observed in the field has been confirmed by treatment of convergence canes data between the roof and floor of several underground quarries. Results show that deformation rate is generally very low. Identifying significant data on incidents over a twenty-year period shows a correlation between main rainfall patterns and surface disorders. On-site alteration processes of chalk and interactions with water show the formation of different patinas on chalk surface. In laboratory, microscopic observations reveal modifications in characteristics of the surface of chalk, mainly calcite precipitation, deposition of iron oxides and hydroxides and porosity modifications.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / No presente resumen

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Mean shift is an effective iterative algorithm widely used in image analysis tasks like tracking, image segmentation, smoothing, filtering, edge detection and etc. It iteratively estimates the modes of the probability function of a set of sample data points based in a region. Mean shift was invented in 1975, but it was not widely used until the work by Cheng in 1995. After that, it becomes popular in computer vision. However the convergence, a key character of any iterative algorithm, has been rigorously proved only very recently, but with strong assumptions. In this thesis, the method of mean shift is introduced systematically first and then the convergence is established under more relaxed assumptions. Finally, generalization of the mean shift method is also given for the estimation of probability density function using generalized multivariate smoothing functions to meet the need for more real life applications.

<p> A review of Stochastic Approximation and the major contributions to the area is made. A proof of convergence for the algorithm is developed. An optimization is attempted on the rate of convergence problem and the uniqueness problem is faced. An alternative proof of convergence is given as an independent check on the first one. Simulation results are present in light of the theory developed, and conclusions, limitations and recommendations are presented. </p> / Thesis / Master of Engineering (MEngr)