The induced 2-tuple linguistic generalized OWA operator and its application in linguistic decision making

[spa] Se presenta el operador de media ponderada ordenada generalizada lingüística de 2 tuplas inducida (2-TILGOWA). Es un nuevo operador de agregación que extiende los anteriores modelos a través de utilizar medias generalizadas, variables de ordenación inducidas e información lingüística representada mediante el modelo de las 2 tuplas lingüísticas. Su principal ventaja se encuentra en la posibilidad de incluir a un gran número de operadores de agregación lingüísticos como casos particulares. Por eso, el análisis puede ser visto desde diferentes perspectivas de forma que se obtiene una visión más completa del problema considerado y seleccionar la alternativa que parece estar en mayor concordancia con nuestros intereses o creencias. A continuación se desarrolla una generalización mayor a través de utilizar medias cuasi-aritméticas, obteniéndose el operador Quasi-2-TILOWA. El trabajo finaliza analizando la aplicabilidad del nuevo modelo en un problema de toma de decisiones sobre gestión de la producción.

Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

Accurate and efficient simulation of multiphase flow in a heterogeneous reservoir by using error estimate and control in the multiscale finite-volume framework

The multiscale finite-volume (MSFV) method is designed to reduce the computational cost of elliptic and parabolic problems with highly heterogeneous anisotropic coefficients. The reduction is achieved by splitting the original global problem into a set of local problems (with approximate local boundary conditions) coupled by a coarse global problem. It has been shown recently that the numerical errors in MSFV results can be reduced systematically with an iterative procedure that provides a conservative velocity field after any iteration step. The iterative MSFV (i-MSFV) method can be obtained with an improved (smoothed) multiscale solution to enhance the localization conditions, with a Krylov subspace method [e.g., the generalized-minimal-residual (GMRES) algorithm] preconditioned by the MSFV system, or with a combination of both. In a multiphase-flow system, a balance between accuracy and computational efficiency should be achieved by finding a minimum number of i-MSFV iterations (on pressure), which is necessary to achieve the desired accuracy in the saturation solution. In this work, we extend the i-MSFV method to sequential implicit simulation of time-dependent problems. To control the error of the coupled saturation/pressure system, we analyze the transport error caused by an approximate velocity field. We then propose an error-control strategy on the basis of the residual of the pressure equation. At the beginning of simulation, the pressure solution is iterated until a specified accuracy is achieved. To minimize the number of iterations in a multiphase-flow problem, the solution at the previous timestep is used to improve the localization assumption at the current timestep. Additional iterations are used only when the residual becomes larger than a specified threshold value. Numerical results show that only a few iterations on average are necessary to improve the MSFV results significantly, even for very challenging problems. Therefore, the proposed adaptive strategy yields efficient and accurate simulation of multiphase flow in heterogeneous porous media.

Iowa Motorcycle Operator Manual,1992.

This manual was developed in cooperation with the Motorcycle Safety Foundation to help you prepare to safely ride a motorcycle. Contains information on motorcycle equipment, safety precautions, laws and earning your license.

Influence of operator experience on performance of ultrasound-guided percutaneous liver biopsy.

The purpose was to evaluate the influence of radiologist's experience on the diagnostic yield and complications of a percutaneous liver biopsy (PLB) method. Six hundred patients underwent an ultrasound-guided PLB by an inexperienced operator in 25.2% of cases (experience of less than 15 percutaneous liver biopsies performed alone--group I) or by an experienced operator (experience of more than 150 percutaneous liver biopsies--group II). The two groups were well-matched with respect to sex, age, percentage with viral hepatitis without histological cirrhosis, number of needle passes, history of liver biopsy and pain before the biopsy. A histological diagnosis was available in 97.3% of cases without any significant difference between the two groups ( P=0.25). However, group II samples were significantly longer and contained more portal tracts ( P=0.01). Pain was mild immediately and 6 h after the biopsy, without significant difference between both groups. Eight vasovagal reactions (five in group II) and one arteriobiliary fistula (in group II) occurred. With the method of PLB used for this study, operator's experience did not influence either the final histological diagnosis or the degree of pain suffered.

Discriminant ECOC: a heuristic method for application dependent design of error correcting output codes

We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result, a compact matrix with high discrimination power is obtained. Our method is validated using the UCI database and applied to a real problem, the classification of traffic sign images.

Subclass problem-dependent design for error-correcting output codes

A common way to model multiclass classification problems is by means of Error-Correcting Output Codes (ECOCs). Given a multiclass problem, the ECOC technique designs a code word for each class, where each position of the code identifies the membership of the class for a given binary problem. A classification decision is obtained by assigning the label of the class with the closest code. One of the main requirements of the ECOC design is that the base classifier is capable of splitting each subgroup of classes from each binary problem. However, we cannot guarantee that a linear classifier model convex regions. Furthermore, nonlinear classifiers also fail to manage some type of surfaces. In this paper, we present a novel strategy to model multiclass classification problems using subclass information in the ECOC framework. Complex problems are solved by splitting the original set of classes into subclasses and embedding the binary problems in a problem-dependent ECOC design. Experimental results show that the proposed splitting procedure yields a better performance when the class overlap or the distribution of the training objects conceal the decision boundaries for the base classifier. The results are even more significant when one has a sufficiently large training size.

Evaluation of the RapidAir 457 Air Void Analyzer, March 2012

An adequate air void system is imperative to produce concrete with freeze-thaw durability in a wet freeze environment such as found in Iowa. Specifications rely on a percentage of air obtained in the plastic state by the pressure meter. Actual, in place air contents, of some concrete pavements in Iowa, have been found with reduced air content due to a number of factors such as excessive vibration and inadequate mixing. Determining hardened air void parameters is a time consuming process involving potential for human error. The RapidAir 457 air void analyzer is an automated device used to determine hardened air void parameters. The device is used in Europe and has been shown to quickly produce accurate and repeatable hardened air results. This research investigates how well the RapidAir 457 results correlate to plastic air content and the image analysis air technique. The repeatability and operator variation were also investigated, as well as, the impact of aggregate porosity and selection of threshold value on hardened air results.

Some spectral properties of the canonical solution operator to $\bar\partial$ on weighted Fock spaces

We characterize the Schatten class membership of the canonical solution operator to $\overline{\partial}$ acting on $L^2(e^{-2\phi})$, where $\phi$ is a subharmonic function with $\Delta\phi$ a doubling measure. The obtained characterization is in terms of $\Delta\phi$. As part of our approach, we study Hankel operators with anti-analytic symbols acting on the corresponding Fock space of entire functions in $L^2(e^{-2\phi})$

Iowa Motorcycle Operator's Manual, 2011

The rules and regualtions for owning and operating a motorcycle in Iowa

Les cegueses del coneixement: l'error i la il·lusió a partir de "El cónsul de sodoma"

Podeu consultar el document complet de la "XVI Setmana de Cinema Formatiu" a: http://hdl.handle.net/2445/22523

Subjetividad humana y "error" en la filosofía cartesiana

El presente trabajo, continuando la línea investigadora acerca de las nociones derazón, conciencia y subjetividad en Descartes, tal como se ha defendido en otros artículos ya publicados, aporta un nuevo argumento a una línea de trabajo previamente iniciada, poniendo de relieve que el problema gnoseológico del error viene condicionado por la misma noción cartesiana de racionalidad, y que ésta dista mucho de lo que tradicionalmente se ha entendido como una racionalidad abstracta y formal, libre de los imperativos humanos. Por otro lado, y a la inversa, también se intenta mostrar como el hecho del error contribuye, cartesianamente hablando, a definir un modelo de racionalidad profundamentehumanizada. El artículo, tras una introducción, se propone analizar las relaciones entre los conceptos básicos de racionalidad, dogma, y naturaleza, lo que permitirá a continuación dejar constancia de la copertenencia entre racionalidad y error, para acabar viendo como la libertad humana es la vez, y para ambos, su fundamento último.

Coocurrencia entre ansiedad y autismo: Las hipótesis del error social y de la carga alostática

Introducción. El concepto de comorbilidad en trastornos del neurodesarrollo como el autismo resulta, en ocasiones, ambiguo. La coocurrencia entre ansiedad y autismo es clínicamente signifi cativa; sin embargo, no siempre es fácil diferenciar si se trata de una comorbilidad"real", donde las dos condiciones comórbidas son fenotípica y etiológicamente idénticas a lo que supondría dicha ansiedad en personas con un desarrollo neurotípico; si se trata de una ansiedad fenotípicamente alterada por los procesos patogénicos de los trastornos del espectro autista, resultando en una variante específica de éstos, o si partimos de una comorbilidad falsa derivada de diagnósticos diferenciales poco exactos. Desarrollo. El artículo plantea dos hipótesis explicativas de dicha coocurrencia, que se retroalimentan entre sí y que no dejan de ser una refl exión en voz alta partiendo de las evidencias científi cas con las que contamos. La primera es la hipótesis del"error social", y considera que el desajuste en el comportamiento social de las personas con autismofruto de alteraciones en los procesos de cognición social contribuye a exacerbar la ansiedad en el autismo. La segunda hipótesis, la de la carga alostática, defi ende que la ansiedad es la respuesta a un estrés crónico, al desgaste o agotamiento que produce la hiperactivación de ciertas estructuras del sistema límbico. Conclusiones. Las manifestaciones prototípicas de la ansiedad presentes en la persona con autismo no siempre se relacionan con las mismas variables biopsicosociales evidenciadas en personas sin autismo. Las evidencias apuntan a respuestas hiperreactivas de huida o lucha (hipervigilancia) cuando la persona se encuentra fuera de su zona de confort, y apoyan la hipótesis del"error social" y de la descompensación del mecanismo de alostasis que permite afrontar el estrés.