985 resultados para Convex Operator


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[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.

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L. S. Shapley, in his paper 'Cores of Convex Games', introduces Convex Measure Games, those that are induced by a convex function on R, acting over a measure on the coalitions. But in a note he states that if this function is a function of several variables, then convexity for the function does not imply convexity of the game or even superadditivity. We prove that if the function is directionally convex, the game is convex, and conversely, any convex game can be induced by a directionally convex function acting over measures on the coalitions, with as many measures as players

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Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.

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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.

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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.

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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 $L^2(e^{-2\phi})$

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L. S. Shapley, in his paper 'Cores of Convex Games', introduces Convex Measure Games, those that are induced by a convex function on R, acting over a measure on the coalitions. But in a note he states that if this function is a function of several variables, then convexity for the function does not imply convexity of the game or even superadditivity. We prove that if the function is directionally convex, the game is convex, and conversely, any convex game can be induced by a directionally convex function acting over measures on the coalitions, with as many measures as players

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We show that any cooperative TU game is the maximum of a finite collection of convex games. This max-convex decomposition can be refined by using convex games with non-negative dividends for all coalitions of at least two players. As a consequence of the above results we show that the class of modular games is a set of generators of the distributive lattice of all cooperative TU games. Finally, we characterize zero-monotonic games using a strong max-convex decomposition

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We study under which conditions the core of a game involved in a convex decomposition of another game turns out to be a stable set of the decomposed game. Some applications and numerical examples, including the remarkable Lucas¿ five player game with a unique stable set different from the core, are reckoning and analyzed.

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

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The multiscale finite-volume (MSFV) method has been derived to efficiently solve large problems with spatially varying coefficients. The fine-scale problem is subdivided into local problems that can be solved separately and are coupled by a global problem. This algorithm, in consequence, shares some characteristics with two-level domain decomposition (DD) methods. However, the MSFV algorithm is different in that it incorporates a flux reconstruction step, which delivers a fine-scale mass conservative flux field without the need for iterating. This is achieved by the use of two overlapping coarse grids. The recently introduced correction function allows for a consistent handling of source terms, which makes the MSFV method a flexible algorithm that is applicable to a wide spectrum of problems. It is demonstrated that the MSFV operator, used to compute an approximate pressure solution, can be equivalently constructed by writing the Schur complement with a tangential approximation of a single-cell overlapping grid and incorporation of appropriate coarse-scale mass-balance equations.

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