906 resultados para Symbolic Computations
Resumo:
New conceptual ideas on network architectures have been proposed in the recent past. Current store-andforward routers are replaced by active intermediate systems, which are able to perform computations on transient packets, in a way that results very helpful for developing and deploying new protocols in a short time. This paper introduces a new routing algorithm, based on a congestion metric, and inspired by the behavior of ants in nature. The use of the Active Networks paradigm associated with a cooperative learning environment produces a robust, decentralized algorithm capable of adapting quickly to changing conditions.
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Objective: Our objective in this paper is to assess diets in the European Union (EU) in relation to the recommendations of the recent World Health Organization/Food and Agriculture Organization expert consultation and to show how diets have changed between 1961 and 2001. Data and methods: Computations make use of FAOSTAT data on food availability at country level linked to a food composition database to convert foods to nutrients. We further explore the growing similarity of diets in the EU by making use of a consumption similarity index. The index provides a single number measure of dietary overlap between countries. Results: The data confirm the excessive consumption by almost all countries of saturated fats, cholesterol and sugars, and the convergence of nutrient intakes across the EU. Whereas in 1961 diets in several European countries were more similar to US diets than to those of other European countries, this is no longer the case; moreover, while EU diets have become more homogeneous, the EU as a whole and the USA have become less similar over time. Conclusions: Although the dominant cause of greater similarity in EU diets over the period studied is increased intakes in Mediterranean countries of saturated fats, cholesterol and sugar, also important are reductions in saturated fat and sugar in some Northern European countries. This suggests that healthy eating messages are finally having an impact on diets; a distinctly European diet may also be emerging.
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Technology involving genetic modification of crops has the potential to make a contribution to rural poverty reduction in many developing countries. Thus far, pesticide-producing Bacillus thuringensis (Bt) varieties of cotton have been the main GM crops under cultivation in developing nations. Several studies have evaluated the farm-level performance of Bt varieties in comparison to conventional ones by estimating production technology, and have mostly found Bt technology to be very successful in raising output and/or reducing pesticide input. However, the production risk properties of this technology have not been studied, although they are likely to be important to risk-averse smallholders. This study investigates the output risk aspects of Bt technology by estimating two 'flexible risk' production function models allowing technology to independently affect the mean and higher moments of output. The first is the popular Just-Pope model and the second is a more general 'damage control' flexible risk model. The models are applied to cross-sectional data on South African smallholders, some of whom used Bt varieties. The results show no evidence that a 'risk-reduction' claim can be made for Bt technology. Indeed, there is some evidence to support the notion that the technology increases output risk, implying that simple (expected) profit computations used in past evaluations may overstate true benefits.
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Population size estimation with discrete or nonparametric mixture models is considered, and reliable ways of construction of the nonparametric mixture model estimator are reviewed and set into perspective. Construction of the maximum likelihood estimator of the mixing distribution is done for any number of components up to the global nonparametric maximum likelihood bound using the EM algorithm. In addition, the estimators of Chao and Zelterman are considered with some generalisations of Zelterman’s estimator. All computations are done with CAMCR, a special software developed for population size estimation with mixture models. Several examples and data sets are discussed and the estimators illustrated. Problems using the mixture model-based estimators are highlighted.
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Aesthetic knowledge comes from practitioners understanding the look, feel, smell, taste and sound of things. It is vital to work in many organizational contexts. In this paper, we explore aesthetic knowledge and knowing in organizations through detailed observation of design work in the architectural practice Edward Cullinan Architects. Through our research, we explore aesthetic knowledge in the context of architectural work, we unpack what it is, how it is generated, and how it is applied in design projects, shared between practitioners and developed at the level of the organization. Our analysis suggests that aesthetic knowledge plays an important part in organizational practice, not only as the symbolic context for work, but as an integral part of the work that people do. It suggests that aesthetic reflexivity, which involves an opening up and questioning of what is known, is experienced as part of practice as well as a `time out' from practice.
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How does the manipulation of visual representations play a role in the practices of generating, evolving and exchanging knowledge? The role of visual representation in mediating knowledge work is explored in a study of design work of an architectural practice, Edward Cullinan Architects. The intensity of interactions with visual representations in the everyday activities on design projects is immediately striking. Through a discussion of observed design episodes, two ways are articulated in which visual representations act as 'artefacts of knowing'. As communication media they are symbolic representations, rich in meaning, through which ideas are articulated, developed and exchanged. Furthermore, as tangible artefacts they constitute material entities with which to interact and thereby develop knowledge. The communicative and interactive properties of visual representations constitute them as central elements of knowledge work. The paper explores emblematic knowledge practices supported by visual representation and concludes by pinpointing avenues for further research.
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The paper is an investigation of the exchange of ideas and information between an architect and building users in the early stages of the building design process before the design brief or any drawings have been produced. The purpose of the research is to gain insight into the type of information users exchange with architects in early design conversations and to better understand the influence the format of design interactions and interactional behaviours have on the exchange of information. We report an empirical study of pre-briefing conversations in which the overwhelming majority of the exchanges were about the functional or structural attributes of space, discussion that touched on the phenomenological, perceptual and the symbolic meanings of space were rare. We explore the contextual features of meetings and the conversational strategies taken by the architect to prompt the users for information and the influence these had on the information provided. Recommendations are made on the format and structure of pre-briefing conversations and on designers' strategies for raising the level of information provided by the user beyond the functional or structural attributes of space.
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This paper draws on ethnographic case-study research conducted amongst a group of first and second generation immigrant children in six inner-city schools in London. It focuses on language attitudes and language choice in relation to cultural maintenance, on the one hand, and career aspirations on the other. It seeks to provide insight into some of the experiences and dilemmatic choices encountered and negotiations engaged in by transmigratory groups, how they define cultural capital, and the processes through which new meanings are shaped as part of the process of defining a space within the host society. Underlying this discussion is the assumption that alternative cultural spaces in which multiple identities and possibilities can be articulated already exist in the rich texture of everyday life amongst transmigratory groups. The argument that whilst the acquisition of 'world languages' is a key variable in accumulating cultural capital, the maintenance of linguistic diversity retains potent symbolic power in sustaining cohesive identities is a recurring theme.
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This study was an attempt to identify the epistemological roots of knowledge when students carry out hands-on experiments in physics. We found that, within the context of designing a solution to a stated problem, subjects constructed and ran thought experiments intertwined within the processes of conducting physical experiments. We show that the process of alternating between these two modes- empirically experimenting and experimenting in thought- leads towards a convergence on scientifically acceptable concepts. We call this process mutual projection. In the process of mutual projection, external representations were generated. Objects in the physical environment were represented in an imaginary world and these representations were associated with processes in the physical world. It is through this coupling that constituents of both the imaginary world and the physical world gain meaning. We further show that the external representations are rooted in sensory interaction and constitute a semi-symbolic pictorial communication system, a sort of primitive 'language', which is developed as the practical work continues. The constituents of this pictorial communication system are used in the thought experiments taking place in association with the empirical experimentation. The results of this study provide a model of physics learning during hands-on experimentation.
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Fast interceptive actions, such as catching a ball, rely upon accurate and precise information from vision. Recent models rely on flexible combinations of visual angle and its rate of expansion of which the tau parameter is a specific case. When an object approaches an observer, however, its trajectory may introduce bias into tau-like parameters that render these computations unacceptable as the sole source of information for actions. Here we show that observer knowledge of object size influences their action timing, and known size combined with image expansion simplifies the computations required to make interceptive actions and provides a route for experience to influence interceptive action.
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Syntactic theory provides a rich array of representational assumptions about linguistic knowledge and processes. Such detailed and independently motivated constraints on grammatical knowledge ought to play a role in sentence comprehension. However most grammar-based explanations of processing difficulty in the literature have attempted to use grammatical representations and processes per se to explain processing difficulty. They did not take into account that the description of higher cognition in mind and brain encompasses two levels: on the one hand, at the macrolevel, symbolic computation is performed, and on the other hand, at the microlevel, computation is achieved through processes within a dynamical system. One critical question is therefore how linguistic theory and dynamical systems can be unified to provide an explanation for processing effects. Here, we present such a unification for a particular account to syntactic theory: namely a parser for Stabler's Minimalist Grammars, in the framework of Smolensky's Integrated Connectionist/Symbolic architectures. In simulations we demonstrate that the connectionist minimalist parser produces predictions which mirror global empirical findings from psycholinguistic research.
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Event-related brain potentials (ERP) are important neural correlates of cognitive processes. In the domain of language processing, the N400 and P600 reflect lexical-semantic integration and syntactic processing problems, respectively. We suggest an interpretation of these markers in terms of dynamical system theory and present two nonlinear dynamical models for syntactic computations where different processing strategies correspond to functionally different regions in the system's phase space.
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The emergence of mental states from neural states by partitioning the neural phase space is analyzed in terms of symbolic dynamics. Well-defined mental states provide contexts inducing a criterion of structural stability for the neurodynamics that can be implemented by particular partitions. This leads to distinguished subshifts of finite type that are either cyclic or irreducible. Cyclic shifts correspond to asymptotically stable fixed points or limit tori whereas irreducible shifts are obtained from generating partitions of mixing hyperbolic systems. These stability criteria are applied to the discussion of neural correlates of consiousness, to the definition of macroscopic neural states, and to aspects of the symbol grounding problem. In particular, it is shown that compatible mental descriptions, topologically equivalent to the neurodynamical description, emerge if the partition of the neural phase space is generating. If this is not the case, mental descriptions are incompatible or complementary. Consequences of this result for an integration or unification of cognitive science or psychology, respectively, will be indicated.
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Finding the smallest eigenvalue of a given square matrix A of order n is computationally very intensive problem. The most popular method for this problem is the Inverse Power Method which uses LU-decomposition and forward and backward solving of the factored system at every iteration step. An alternative to this method is the Resolvent Monte Carlo method which uses representation of the resolvent matrix [I -qA](-m) as a series and then performs Monte Carlo iterations (random walks) on the elements of the matrix. This leads to great savings in computations, but the method has many restrictions and a very slow convergence. In this paper we propose a method that includes fast Monte Carlo procedure for finding the inverse matrix, refinement procedure to improve approximation of the inverse if necessary, and Monte Carlo power iterations to compute the smallest eigenvalue. We provide not only theoretical estimations about accuracy and convergence but also results from numerical tests performed on a number of test matrices.
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Exact error estimates for evaluating multi-dimensional integrals are considered. An estimate is called exact if the rates of convergence for the low- and upper-bound estimate coincide. The algorithm with such an exact rate is called optimal. Such an algorithm has an unimprovable rate of convergence. The problem of existing exact estimates and optimal algorithms is discussed for some functional spaces that define the regularity of the integrand. Important for practical computations data classes are considered: classes of functions with bounded derivatives and Holder type conditions. The aim of the paper is to analyze the performance of two optimal classes of algorithms: deterministic and randomized for computing multidimensional integrals. It is also shown how the smoothness of the integrand can be exploited to construct better randomized algorithms.