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We consider a Hilbert boundary value problem with an unknown parametric function on arbitrary infinite straight line passing through the origin. We propose to transform the Hilbert boundary value problem to Riemann boundary value problem, and address it by defining symmetric extension for holomorphic functions about an arbitrary straight line passing through the origin. Finally, we develop the general solution and the solvable conditions for the Hilbert boundary value problem.
We considered a kind of singular integral operator with Weierstrass function kernel on a simple closed smooth curve in a fundamental period parallelogram. Using the method of complex functions, we established the Bertrand Poincaré formula for changing order of the corresponding integration, and some important properties for this kind of singular integral operator.
Various kinds of Riemann boundary value problems (BVPs) for analytic functions on closed curves or on open arc, doubly periodic Riemann BVPs, doubly quasi-periodic Riemann BVPs, and BVPs for polyanalytic functions have been widely investigated in [1-8]. The main ap- proach is to use the decomposition of polyanalytic functions and their generalization to transform the boundary value problems to their corresponding boundary value problems for analytic functions. Recently, inverse Riemann BVPs for generalized analytic functions or bianalytic functions have been investigated in [9-12].
In this paper, we consider a kind of Riemann BVP of non-normal type on the infinite straight line and discuss the solvable conditions and the general solution for it.
negotiation plays an important role in B2C e-commerce. There is a paucity of
further scientific investigation and a pressing need on designing the software
agent that can deal with the human’s random and dynamic offer, which is
crucially useful in human-computer negotiation to achieve better online
negotiation outcomes. The lack of such studies has decelerated the process of
applying automated negotiation to real world applications. To address the
critical issue, this paper develops a dynamic time-dependent strategy
concession model, that can predict the human’s negotiation behavior during the
process of the negotiation. To demonstrate the effectiveness of this model, we
implement a prototype and conduct human-computer negotiations over 121
subjects. The experimental analysis not only confirms our model’s effect but
also reveals some insights into future work about human-computer negotiation