Tightly controlled linear hashing without separate overflow storage

A hashing method is presented where the amount of storage required for a file can expand and shrink by very large factors. The performance of this method as measured by lookup time, insertion time and deletion time is very good even when the total storage utilization is as high as 90 percent. The user can completely control the storage utilization between two chosen bounds so that the storage requirement varies linearly with the number of records currently in the file.Unlike previous methods, no separate overflow storage pool is involved and one need not be concerned with expected and worst case requirements for overflow space. Indeed, the absence of requirements for such a separate overflow pool could allow the use of this method with primitive microprocessor operating systems.The choice of hashing functions is discussed and simulation results show great danger in blindly using the popular remainder method.Both an elementary analysis and simulation results are given.This research was supported by the National Science and Engineering Research Council of Canada.     

Differential equation approach for the energy average of the scattering function

An exact differential equation is given to evaluate the energy average of the scattering function. The advantage of the differential equation as compared to the earlier methods based on series expansion is that one has to evaluate only single sums over the complex poles of the S-matrix. Using Wigner’s semicircle law for the distribution of the real parts of the poles of the scattering matrix, the earlier expression for the energy average of the scattering function is rederived.     

GRCA(1)模型中误差方差自加权估计的渐近分布

考虑随机系数自回归模型Y_t =Φ_ty_t-1+ u_t,其中 Φ_t为随机系数,u_t为随机误差。在允许Φ_t与u_t相依以及Eu_t无穷的条件下,构造了误差方差的自加权估计,并证明了该估计的渐近正态性。最后通过数值模拟,说明 自加权估计的稳健和有效性。     

On Hsu's theorem in multivariate regression

The paper deals with optimal quadratic unbiased estimation of the unknown dispersion matrix in multivariate regression models without assuming normality of the errors. We show that Hsu's theorem for univariate regression models continues to multivariate models with no additional assumptions. Furthermore optimal quadratic plus linear estimating functions for regression coefficients are considered, and we investigate whether the ordinary linear estimates are the best. This leads to a new theorem which is similar to that of Hsu.     

Nonconical optimality conditions: Some additional results

The purpose of the present note is to provide a somewhat more flexible statement of the sufficiency conditions in Section 4 of Ref. 1 and to give explicit statements of the fundamental necessity and sufficiency results, which were only implicitly presented there. The additional flexibility is obtained by considering local, rather than global, pseudoconcavity requirements.     

Electrode Kinetics of Lead in N-(3-Aminopropyl)-Diethanolamine Solution at the Dropping Mercury Electrode

The lead complex of N-(3-Aminopropyl)-Diethanolamine (APDEA) was investigated polarographically over the pH range 10.40-12-85 and ligand concentration 0.0227-1.002M. A quasi-reversible and diffusion-controlled reduction wave was obtained at pH≥10.40. The electron-transfer coefficient and rate constants were determined as 0.11-0.34 and 10^?4 cmsec^?1, respectively.     

Generalizations of Quantum Mechanics Induced by Classical Statistical Field Theory

No Heading We show that the Dirac-von Neumann formalism for quantum mechanics can be obtained as an approximation of classical statistical field theory. This approximation is based on the Taylor expansion (up to terms of the second order) of classical physical variables – maps f : Ω → R, where Ω is the infinite-dimensional Hilbert space. The space of classical statistical states consists of Gaussian measures ρ on Ω having zero mean value and dispersion σ²(ρ) ≈ h. This viewpoint to the conventional quantum formalism gives the possibility to create generalized quantum formalisms based on expansions of classical physical variables in the Taylor series up to terms of nth order and considering statistical states ρ having dispersion σ²(ρ) = hⁿ (for n = 2 we obtain the conventional quantum formalism).