904 resultados para Spaces of measurable functions
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Utilising de Certeau's concepts of daily life and his delineation between strategies and tactics as everyday practices this paper examines the role of informal economies in post-Ukraine. Based on 700 household surveys and seventy-five in-depth interviews, conducted in three Ukrainian cities, the paper argues that individuals/households have developed a wide range of tactics in response to the economic marginalisation the country has endured since the collapse of the Soviet Union. Firstly, the paper details the importance of informal economies in contemporary Ukraine while highlighting that many such practices are operated out of necessity due to low wage and pension rates and high levels of corruption. This challenges state-produced statistics on the scale of economic marginalisation currently experienced in the country. By exploring a variety of these tactics the paper then examines how unequal power relations shape the spaces in which these practices operate in and how they can be simultaneously sites of exploitation and resistance to economic marginalisation. The paper concludes pessimistically by suggesting that the way in which these economic spaces are shaped precludes the development of state policies which might benefit the economically marginalised.
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This essay examines how academics and students in England have been primed to comply with a political agenda of “deep” neoliberalization through cumulative processes of institutional and subjective undermining and considers what might be an appropriate logic of critical response. It first describes how the embedding of principles and mechanisms of market governance within academic life has depoliticized methods for critically theorizing and collectively resisting these processes and then explores the work of recent student-led opposition to the British government’s new policies, teasing out some theoretical implications of the logic of occupation being cultivated there. It suggests that by fusing a determination for autonomy with a transgressive cultivation of new forms of thinking and social practice, the occupations illustrate new critical-experimental work in the politics of possibility. The underlying logic thus offers some resources for reimagining modalities of resistance to processes of deep neoliberalization; however, becoming receptive to them may also require a critique of professional academic subjectivities and reevaluation of attachments to existing forms of the university itself.
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We propose and investigate a method for the stable determination of a harmonic function from knowledge of its value and its normal derivative on a part of the boundary of the (bounded) solution domain (Cauchy problem). We reformulate the Cauchy problem as an operator equation on the boundary using the Dirichlet-to-Neumann map. To discretize the obtained operator, we modify and employ a method denoted as Classic II given in [J. Helsing, Faster convergence and higher accuracy for the Dirichlet–Neumann map, J. Comput. Phys. 228 (2009), pp. 2578–2576, Section 3], which is based on Fredholm integral equations and Nyström discretization schemes. Then, for stability reasons, to solve the discretized integral equation we use the method of smoothing projection introduced in [J. Helsing and B.T. Johansson, Fast reconstruction of harmonic functions from Cauchy data using integral equation techniques, Inverse Probl. Sci. Eng. 18 (2010), pp. 381–399, Section 7], which makes it possible to solve the discretized operator equation in a stable way with minor computational cost and high accuracy. With this approach, for sufficiently smooth Cauchy data, the normal derivative can also be accurately computed on the part of the boundary where no data is initially given.
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We consider the problem of stable determination of a harmonic function from knowledge of the solution and its normal derivative on a part of the boundary of the (bounded) solution domain. The alternating method is a procedure to generate an approximation to the harmonic function from such Cauchy data and we investigate a numerical implementation of this procedure based on Fredholm integral equations and Nyström discretization schemes, which makes it possible to perform a large number of iterations (millions) with minor computational cost (seconds) and high accuracy. Moreover, the original problem is rewritten as a fixed point equation on the boundary, and various other direct regularization techniques are discussed to solve that equation. We also discuss how knowledge of the smoothness of the data can be used to further improve the accuracy. Numerical examples are presented showing that accurate approximations of both the solution and its normal derivative can be obtained with much less computational time than in previous works.
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In this paper we investigate the Boolean functions with maximum essential arity gap. Additionally we propose a simpler proof of an important theorem proved by M. Couceiro and E. Lehtonen in [3]. They use Zhegalkin’s polynomials as normal forms for Boolean functions and describe the functions with essential arity gap equals 2. We use to instead Full Conjunctive Normal Forms of these polynomials which allows us to simplify the proofs and to obtain several combinatorial results concerning the Boolean functions with a given arity gap. The Full Conjunctive Normal Forms are also sum of conjunctions, in which all variables occur.
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In this paper we examine discrete functions that depend on their variables in a particular way, namely the H-functions. The results obtained in this work make the “construction” of these functions possible. H-functions are generalized, as well as their matrix representation by Latin hypercubes.
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∗Participant in Workshop in Linear Analysis and Probability, Texas A & M University, College Station, Texas, 2000. Research partially supported by the Edmund Landau Center for Research in Mathematical Analysis and related areas, sponsored by Minerva Foundation (Germany).
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In this paper an alternative characterization of the class of functions called k -uniformly convex is found. Various relations concerning connections with other classes of univalent functions are given. Moreover a new class of univalent functions, analogous to the ’Mocanu class’ of functions, is introduced. Some results concerning this class are derived.
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∗ The present article was originally submitted for the second volume of Murcia Seminar on Functional Analysis (1989). Unfortunately it has been not possible to continue with Murcia Seminar publication anymore. For historical reasons the present vesion correspond with the original one.
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First order characterizations of pseudoconvex functions are investigated in terms of generalized directional derivatives. A connection with the invexity is analysed. Well-known first order characterizations of the solution sets of pseudolinear programs are generalized to the case of pseudoconvex programs. The concepts of pseudoconvexity and invexity do not depend on a single definition of the generalized directional derivative.
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The problem of decision functions quality in pattern recognition is considered. An overview of the approaches to the solution of this problem is given. Within the Bayesian framework, we suggest an approach based on the Bayesian interval estimates of quality on a finite set of events.
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The problem of sequent two-block decomposition of a Boolean function is regarded in case when a good solution does exist. The problem consists mainly in finding an appropriate weak partition on the set of arguments of the considered Boolean function, which should be decomposable at that partition. A new fast heuristic combinatorial algorithm is offered for solving this task. At first the randomized search for traces of such a partition is fulfilled. The recognized traces are represented by some "triads" - the simplest weak partitions corresponding to non-trivial decompositions. After that the whole sought-for partition is restored from the discovered trace by building a track initialized by the trace and leading to the solution. The results of computer experiments testify the high practical efficiency of the algorithm.
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Mathematics Subject Classification: 26A16, 26A33, 46E15.
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2000 Mathematics Subject Classification: Primary 26A33, 30C45; Secondary 33A35