音像业全球化趋势与我国音像业对外经贸策略的创新

在音像业全球化趋势下,尤其是随着加入WTO,我国音像业在对外经贸策略和规章方面存在的诸多问题日益暴露出来。因此,针对我国音像业对外经贸策略的不足,积极对音像业对外经贸策略进行创新,具有重要的理论价值和现实意义。     

DRTC＋＋：一个面向对象的分布式实时程序设计语言

提出了一个面向对象的分布式实时程序设计语言ＤＲＴＣ＋＋。它是在Ｃ＋＋语言的基础上进行了扩充，增加了分布功能和通信功能，引入了活跃对象、共享对象、活跃对象的时间封装机制、对象的访问权限等功能。ＤＲＴＣ＋＋语言有简洁的文法和清晰的语义。     

绿色带型工业城构想

我国城市空气污染与城市工业规划密切相关。因此，新建或改建中小城市的工业规划区域，决不能再走“工业污染城市”的老路，应以科学发展观和可持续发展的理念，在总结了有关城市工业污染教训的基础上，特别是吸取了天津开发区工业社会化服务中心建设的经验，按照新的规划要求，提出了工业与城市同步发展的无有害气体污染的新型绿色带型工业城的构想。     

混合线性分式目标规划的一般解法及其应用

线性分式目标规划是近几年发展起来的目标规划的新分支,尚无一般解法。本文给出了混合线性分式目标规划的一般解法及其应用实例。     

Decomposing the predictive performance of the moving average trading rule of technical analysis: the contribution of linear and non-linear dependencies in stock returns

The main purpose of this work is to decompose the predictive performance of the moving average (MA) trading rule and find out the portion that could be attributed to the possible exploitation of linear and non-linear dependencies in stock returns. Data from the General Index of the Athens Stock Exchange, from the Standard and Poor-500 Index of the New York Stock Exchange and from the Austrian Traded Index of the Vienna Stock Exchange are filtered by linear filters so as the resulting simulated ‘returns’ exhibit no serial correlation. Applying MA trading rules to both the original and the simulated indices and using a new statistical testing procedure that takes into account the sensitivity of the performance of the trading rule as a function of the length of the MA it is found that the predictive performance of the trading rule is clearly weakened when applied to the simulated indices indicating that a substantial part of the rule's predictive performance is due to the exploitation of linear dependencies in stock returns. This weakening is uneven; in general the shorter the MA length the more pronounced the attenuation.     

Flexible Copula Density Estimation with Penalized Hierarchical B‐splines

The paper introduces a new method for flexible spline fitting for copula density estimation. Spline coefficients are penalized to achieve a smooth fit. To weaken the curse of dimensionality, instead of a full tensor spline basis, a reduced tensor product based on so called sparse grids (Notes Numer. Fluid Mech. Multidiscip. Des., 31, 1991, 241‐251) is used. To achieve uniform margins of the copula density, linear constraints are placed on the spline coefficients, and quadratic programming is used to fit the model. Simulations and practical examples accompany the presentation.     

An algorithm for the minimum sum of weighted absolute errors regression

We propose an algorithm to estimate the unknown constants in a multiple linear regression model under the minimum sum of weighted absolute errors (MSWAE). The proposed algorithm, a generalization of an earlier algorithm, is compared to a bounded variable algorithm. Some somputational experience is reported.     

Selection of cost-optimal 2k−p fractional factorials

Selecting an optimal 2^k?pfractional factorial is structured as a mathematical programming problem. An algorithm is defined for the solution, and the case of additive costs is shown to have a known solution for resolution III designs.     

Selective Maintenance in System Reliability with Random Costs of Repairing and Replacing the Components

In this paper we consider the problem of determining the optimum number of repairable and replaceable components to maximize a system's reliability when both, the cost of repairing the components and the cost of replacement of components by new ones, are random. We formulate it as a problem of non-linear stochastic programming. The solution is obtained through Chance Constrained programming. We also consider the problem of finding the optimal maintenance cost for a given reliability requirement of the system. The solution is then obtained by using Modified E-model. A numerical example is solved for both the formulations.     

A Combined Nonlinear Programming Model and Kibria Method for Choosing Ridge Parameter Regression

Ridge regression solves multicollinearity problems by introducing a biasing parameter that is called ridge parameter; it shrinks the estimates as well as their standard errors in order to reach acceptable results. Many methods are available for estimating a ridge parameter. This article has considered some of these methods and also proposed a combined nonlinear programming model and Kibria method. A simulation study has been made to evaluate the performance of the proposed estimators based on the minimum mean squared error criterion. The simulation study indicates that under certain conditions the proposed estimators outperform the least squares (LS) estimators and other popular existing estimators. Moreover, the new proposed model is applied on dataset that suffers also from the presence of heteroscedastic errors.