998 resultados para Creative class


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A large class of special functions are solutions of systems of linear difference and differential equations with polynomial coefficients. For a given function, these equations considered as operator polynomials generate a left ideal in a noncommutative algebra called Ore algebra. This ideal with finitely many conditions characterizes the function uniquely so that Gröbner basis techniques can be applied. Many problems related to special functions which can be described by such ideals can be solved by performing elimination of appropriate noncommutative variables in these ideals. In this work, we mainly achieve the following: 1. We give an overview of the theoretical algebraic background as well as the algorithmic aspects of different methods using noncommutative Gröbner elimination techniques in Ore algebras in order to solve problems related to special functions. 2. We describe in detail algorithms which are based on Gröbner elimination techniques and perform the creative telescoping method for sums and integrals of special functions. 3. We investigate and compare these algorithms by illustrative examples which are performed by the computer algebra system Maple. This investigation has the objective to test how far noncommutative Gröbner elimination techniques may be efficiently applied to perform creative telescoping.

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There are numerous text documents available in electronic form. More and more are becoming available every day. Such documents represent a massive amount of information that is easily accessible. Seeking value in this huge collection requires organization; much of the work of organizing documents can be automated through text classification. The accuracy and our understanding of such systems greatly influences their usefulness. In this paper, we seek 1) to advance the understanding of commonly used text classification techniques, and 2) through that understanding, improve the tools that are available for text classification. We begin by clarifying the assumptions made in the derivation of Naive Bayes, noting basic properties and proposing ways for its extension and improvement. Next, we investigate the quality of Naive Bayes parameter estimates and their impact on classification. Our analysis leads to a theorem which gives an explanation for the improvements that can be found in multiclass classification with Naive Bayes using Error-Correcting Output Codes. We use experimental evidence on two commonly-used data sets to exhibit an application of the theorem. Finally, we show fundamental flaws in a commonly-used feature selection algorithm and develop a statistics-based framework for text feature selection. Greater understanding of Naive Bayes and the properties of text allows us to make better use of it in text classification.

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We present a novel scheme ("Categorical Basis Functions", CBF) for object class representation in the brain and contrast it to the "Chorus of Prototypes" scheme recently proposed by Edelman. The power and flexibility of CBF is demonstrated in two examples. CBF is then applied to investigate the phenomenon of Categorical Perception, in particular the finding by Bulthoff et al. (1998) of categorization of faces by gender without corresponding Categorical Perception. Here, CBF makes predictions that can be tested in a psychophysical experiment. Finally, experiments are suggested to further test CBF.

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Most psychophysical studies of object recognition have focussed on the recognition and representation of individual objects subjects had previously explicitely been trained on. Correspondingly, modeling studies have often employed a 'grandmother'-type representation where the objects to be recognized were represented by individual units. However, objects in the natural world are commonly members of a class containing a number of visually similar objects, such as faces, for which physiology studies have provided support for a representation based on a sparse population code, which permits generalization from the learned exemplars to novel objects of that class. In this paper, we present results from psychophysical and modeling studies intended to investigate object recognition in natural ('continuous') object classes. In two experiments, subjects were trained to perform subordinate level discrimination in a continuous object class - images of computer-rendered cars - created using a 3D morphing system. By comparing the recognition performance of trained and untrained subjects we could estimate the effects of viewpoint-specific training and infer properties of the object class-specific representation learned as a result of training. We then compared the experimental findings to simulations, building on our recently presented HMAX model of object recognition in cortex, to investigate the computational properties of a population-based object class representation as outlined above. We find experimental evidence, supported by modeling results, that training builds a viewpoint- and class-specific representation that supplements a pre-existing repre-sentation with lower shape discriminability but possibly greater viewpoint invariance.

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To recognize a previously seen object, the visual system must overcome the variability in the object's appearance caused by factors such as illumination and pose. Developments in computer vision suggest that it may be possible to counter the influence of these factors, by learning to interpolate between stored views of the target object, taken under representative combinations of viewing conditions. Daily life situations, however, typically require categorization, rather than recognition, of objects. Due to the open-ended character both of natural kinds and of artificial categories, categorization cannot rely on interpolation between stored examples. Nonetheless, knowledge of several representative members, or prototypes, of each of the categories of interest can still provide the necessary computational substrate for the categorization of new instances. The resulting representational scheme based on similarities to prototypes appears to be computationally viable, and is readily mapped onto the mechanisms of biological vision revealed by recent psychophysical and physiological studies.

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We report on a new class of nonionic, photosensitive surfactants consisting of a polar di(ethylene oxide) head group attached to an alkyl spacer of between two and eight methylene groups, coupled through an ether linkage to an azobenzene moiety. Structural changes associated with the interconversion of the azobenzene group between its cis and trans forms as mediated by the wavelength of an irradiating light source cause changes in the surface tension and self-assembly properties. Differences in saturated surface tensions (surface tension at concentrations above the CMC) were as high as 14.4 mN/m under radiation of different wavelengths. The qualitative behavior of the surfactants changed as the spacer length changed, attributed to the different orientations adopted by the different surfactants depending on their isomerization states, as revealed by neutron reflection studies. The self-assembly of these photosensitive surfactants has been investigated by light scattering, small angle neutron scattering, and cryo-TEM under different illuminations. The significant change in the self-assembly in response to different illumination conditions was attributed to the sign change in Gaussian rigidity, which originated from the azobenzene photoisomerization.

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Las sesiones de laboratorio ofrecen la posibilidad de simular a pequeña escala el proceso de investigación. En una actividad formativa basada en la metodología PBL (Problem Based Learning), cada grupo de alumnos recibe el encargo de comprobar de manera experimental el efecto de una sustancia sobre el crecimiento de una población de la planta acuática Lemna minor. Después de completar el diseño experimental y llevar a cabo el ensayo, los alumnos deben redactar un informe final en formato póster de forma que presenten sintéticamente los objetivos del ensayo, el procedimiento experimental seguido, los resultados obtenidos y las conclusiones alcanzadas. La actividad finaliza con la presentación de todos los pósters en una sesión específica. Esta práctica docente ha permitido detectar algunos déficits formativos en nuestros alumnos que han motivado la implementación de estrategias correctoras

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This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory

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El uso de las licencias Creative Commons es muy amplio, puede darse respecto de cualquiera de las obras protegidas por el derecho de autor y por tanto ser aplicado por artistas, escritores, científicos, profesores, estudiantes, oficinistas, etc. Sin embargo, el ejercicio de análisis y comparación que proponemos respecto al uso de licencias Creative Commons es para un escenario más cerrado que pueda atender a los intereses propios del sector al que va dirigida esta publicación en particular, es decir, al objeto de trabajo de las Editoriales Universitarias en América Latina, a las publicaciones académicas. Por tanto, este documento se ocupará concretamente del uso de las licencias Creative Commons[1] en las publicaciones académicas en línea, mirándolas desde la óptica del acceso abierto (Labastida i Juan; Iglesias, 2006) y pensándolas desde la filosofía que las perfila, su penetración, las oportunidades que generan, las ventajas que hacen evidentes, e incluso los retos y desventajas que afrontan.

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A combination of perl scripts and LaTeX files, this generates multiple multiple choice class tests from a single set of questions. You input a list of questions and answers into a text file. The script then produces any number of class tests that can be used, together with master answer sheets, by scrambling the order of the questions and the answers. Includes a detailed README file, but best just to try it and see.

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This is the first part of a 2 part video from my talk in May 2008 on open source content creation.

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This is the second part of a 2 part video from my talk in May 2008 on open source content creation. Here I am talking about the Making of Doljer

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My profile page on creative commons network

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Slides for a Level 3 Digital Practice and Theory lecture on using CC, promoting your work and ways to get it out there, some demonstration on the economic value of sharing.

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slides plus mark scheme and link to group work videos