Aplicación del control estadístico a la variable crítica temperatura en una empresa acerera.

Tesis (Master en Administración y de Negocios con Especialidad en Producción y Calidad) UANL, 2009.

Étude in vivo de la relation entre la structure et la fonction de la boucle variable de l'ARN de transfert de la sélénocystéine d'E. coli

La sélénocystéine est le 21e acide aminé encodé génétiquement et on la retrouve à travers les trois domaines de la vie. Elle est synthétisée sur l'ARNtSec par un processus unique. L'ARNtSec se distingue également au niveau structural. La tige acceptrice possède 8 (procaryotes) et 9 (eucaryotes) paires de bases, contrairement aux ARNt canoniques qui ont invariablement 7 paires de bases dans la tige acceptrice. De plus, la tige D a 2 paires de bases additionnelles qui remplacent les interactions tertiaires universelles 8-14, 15-48 qui sont absentes chez l'ARNtSec. D'autre part, la longueur de la boucle variable de l'ARNtSec est plus longue que la majorité des ARNt de type II. Dans ce mémoire, on se concentre sur la région de la boucle variable de l'ARNtSec . La recherche consiste à distinguer les paires de bases de la boucle variable qui sont essentielles à la biosynthèse et l’insertion de la sélénocystéine. De plus, on regarde si la paire de base additionnelle de la tige acceptrice de l'ARNtSec (procaryote) est essentielle pour l'insertion de la sélénocystéine. Pour répondre à ces questions, on a utilisé l'approche expérimentale Évolution Instantanée qui consiste au criblage in vivo d'ARNtSec fonctionnels chez E. coli. Dans ce travail, on montre que l'insertion de la sélénocystéine ne nécessite pas une spécificité de la longueur ou de la séquence de l'ARNtSec. On montre aussi que ni la longueur de la tige acceptrice ou du domaine tige acceptrice/tige T n'est essentielle pour avoir un ARNtSec fonctionnel.

Estimating Dependency Structure as a Hidden Variable

This paper introduces a probability model, the mixture of trees that can account for sparse, dynamically changing dependence relationships. We present a family of efficient algorithms that use EMand the Minimum Spanning Tree algorithm to find the ML and MAP mixtureof trees for a variety of priors, including the Dirichlet and the MDL priors.

Estimating Dependency Structure as a Hidden Variable

This paper introduces a probability model, the mixture of trees that can account for sparse, dynamically changing dependence relationships. We present a family of efficient algorithms that use EM and the Minimum Spanning Tree algorithm to find the ML and MAP mixture of trees for a variety of priors, including the Dirichlet and the MDL priors. We also show that the single tree classifier acts like an implicit feature selector, thus making the classification performance insensitive to irrelevant attributes. Experimental results demonstrate the excellent performance of the new model both in density estimation and in classification.

ControlFluid: un mercado variable

Las estrategias de una empresa en un mercado pequeño donde hay pocos compradores y muchos vendedores se vuelven el centro y punto clave de éxito, de lo contrario la empresa solo sigue una tendencia de mercado que al mediano plazo no resultara efectiva y terminan desapareciendo. Es por ello que las estrategias de mercado en las empresas se vuelven la característica diferenciadora permitiendo tomar ventaja del hacinamiento de un sector. Para que una empresa sea exitosa debe tener en cuenta sus ventajas competitivas y potencializarlas al máximo según las condiciones del mercado en el que se desempeña, ya sean estas de estructura, recursos o talento humano. El estudio de caso pretende abordar las dinámicas de un mercado específico con tendencias particulares que definen la forma de competir y las costumbres de sus principales actores. Estas mismas tendencias fijan los modelos de negocio en el sector, que desde diversos análisis como el PESTEL o puntos de vista de autores como Kotler (1992) y sus estrategias competitivas según la participación de mercado o Miller (1986) y sus definiciones de mercados o Porter (1980) con sus fuerzas de mercado, lo que permite dar una guía o explicación del porqué de las situaciones particulares del mercado en un sector tan especifico como el de automatización y control de calidad.

A regime-dependent balanced control variable based on potential vorticity

In this paper it is argued that rotational wind is not the best choice of leading control variable for variational data assimilation, and an alternative is suggested and tested. A rotational wind parameter is used in most global variational assimilation systems as a pragmatic way of approximately representing the balanced component of the assimilation increments. In effect, rotational wind is treated as a proxy for potential vorticity, but one that it is potentially not a good choice in flow regimes characterised by small Burger number. This paper reports on an alternative set of control variables which are based around potential vorticity. This gives rise to a new formulation of the background error covariances for the Met Office's variational assimilation system, which leads to flow dependency. It uses similar balance relationships to traditional schemes, but recognises the existence of unbalanced rotational wind which is used with a new anti-balance relationship. The new scheme is described and its performance is evaluated and compared to a traditional scheme using a sample of diagnostics.

Control of framework stoichiometry in MeGaPO laumontites using 1-methylimidazole as structure-directing agent

A series of heterometal substituted gallium phosphates, (N2C4H7)(0.5+x)[Me0.5+xGa2.5-x(PO4)(3)] (Me = Mn, Fe, Co and Zn, x approximate to 0.25), has been synthesised under solvothermal conditions at 433 K in ethylene glycol using I-methylimidazole as a templating agent and their structures determined at 150 K using single-crystal X-ray diffraction. The compounds are isostructural, crystallising in the monoclinic space group C 2/c, with lattice parameters ca. 15 x 13 x 15 angstrom and beta = 112 degrees, and adopt the laumontite framework type (LAU). The incorporation of 1-methylimidazole cations into the one-dimensional pore systems of these materials is about three quarters the uptake value obtained previously for the less-bulky amine cations of imidazole and pyridine in other MeGaPO laumontites, which have the formula (TH)[MeGa2(PO4)(3)] (Me = Mn, Fe, Co and Zn; T = C5H5N and C3N2H4). The size, shape and charge of the amine clearly influence both the metal-phosphate framework stoichiometry (i.e. Me2+:Ga3+ ratio) and the framework charge. (C) 2007 Elsevier Inc. All rights reserved.

A novel technique for differentiation of proteins in the development of acid gel structure from control and heat treated milk using confocal scanning laser microscopy

The incorporation of caseins and whey proteins into acid gels produced from unheated and heat treated skimmed milk was studied by confocal scanning laser microscopy (CSLM) using fluorescent labelled proteins. Bovine casein micelles were labelled using Alexa Fluor 594, while whey proteins were labelled using Alexa Fluor 488. Samples of the labelled protein solutions were introduced into aliquots of pasteurised skim milk, and skim milk heated to 90 degrees C for 2 min and 95 degrees C for 8 min. The milk was acidified at 40 degrees C to a final pH of 4.4 using 20 g gluconodelta-lactone/l (GDL). The formation of gels was observed with CSLM at two wavelengths (488 nm and 594 nm), and also by visual and rheological methods. In the control milk, as pH decreased distinct casein aggregates appeared, and as further pH reduction occurred, the whey proteins could be seen to coat the casein aggregates. With the heated milks, the gel structure was formed of continuous strands consisting of both casein and whey protein. The formation of the gel network was correlated with an increase in the elastic modulus for all three treatments, in relation to the severity of heat treatment. This model system allows the separate observation of the caseins and whey proteins, and the study of the interactions between the two protein fractions during the formation of the acid gel structure, on a real-time basis. The system could therefore be a valuable tool in the study of structure formation in yoghurt and other dairy protein systems.

A mixture of experts network structure construction algorithm for modelling and control

This paper introduces a new fast, effective and practical model structure construction algorithm for a mixture of experts network system utilising only process data. The algorithm is based on a novel forward constrained regression procedure. Given a full set of the experts as potential model bases, the structure construction algorithm, formed on the forward constrained regression procedure, selects the most significant model base one by one so as to minimise the overall system approximation error at each iteration, while the gate parameters in the mixture of experts network system are accordingly adjusted so as to satisfy the convex constraints required in the derivation of the forward constrained regression procedure. The procedure continues until a proper system model is constructed that utilises some or all of the experts. A pruning algorithm of the consequent mixture of experts network system is also derived to generate an overall parsimonious construction algorithm. Numerical examples are provided to demonstrate the effectiveness of the new algorithms. The mixture of experts network framework can be applied to a wide variety of applications ranging from multiple model controller synthesis to multi-sensor data fusion.

Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks

An input variable selection procedure is introduced for the identification and construction of multi-input multi-output (MIMO) neurofuzzy operating point dependent models. The algorithm is an extension of a forward modified Gram-Schmidt orthogonal least squares procedure for a linear model structure which is modified to accommodate nonlinear system modeling by incorporating piecewise locally linear model fitting. The proposed input nodes selection procedure effectively tackles the problem of the curse of dimensionality associated with lattice-based modeling algorithms such as radial basis function neurofuzzy networks, enabling the resulting neurofuzzy operating point dependent model to be widely applied in control and estimation. Some numerical examples are given to demonstrate the effectiveness of the proposed construction algorithm.

An LMS style variable tap-length algorithm for structure adaptation

Searching for the optimum tap-length that best balances the complexity and steady-state performance of an adaptive filter has attracted attention recently. Among existing algorithms that can be found in the literature, two of which, namely the segmented filter (SF) and gradient descent (GD) algorithms, are of particular interest as they can search for the optimum tap-length quickly. In this paper, at first, we carefully compare the SF and GD algorithms and show that the two algorithms are equivalent in performance under some constraints, but each has advantages/disadvantages relative to the other. Then, we propose an improved variable tap-length algorithm using the concept of the pseudo fractional tap-length (FT). Updating the tap-length with instantaneous errors in a style similar to that used in the stochastic gradient [or least mean squares (LMS)] algorithm, the proposed FT algorithm not only retains the advantages from both the SF and the GD algorithms but also has significantly less complexity than existing algorithms. Both performance analysis and numerical simulations are given to verify the new proposed algorithm.