利用正交直积态的量子密钥分配协议

基于量子密钥分配协议是目前实现密钥分配最安全的方法,两个三态量子位组成的复合系统中存在一组正交直积态,它可以表现出非定域性。该文提出了一个建立在该系统的非定域性基础上的量子密钥分配协议,协议双方通过交换量子位和集体测量建立起共享的密钥。量子力学的基本原理保证了该协议是无条件安全的,没有第三方可以窃取密钥而不被发现。该协议不需要纠缠态,也不需要做任何量子操作。因此,它更容易在实践中实现,同时具有更高的可靠性与健壮性。     

EQUINEIGHBOURED XPERIMENTAL DESIGNS

This paper introduces a new class of designs called equi-neighboured designs. An equineighboured design has the property that every unordered pair of treatments occurs as nearest neighbours equally frequently at every level. These designs are defined in Section 4 and shown to be balanced when neighbouring observations are correlated. Some equineighboured designs are constructed using a complete set of orthogonal Latin squares. Cyclic equineighboured designs are also defined.     

Estimating Mixing Densities in Exponential Family Models for Discrete Variables

This paper is concerned with estimating a mixing density g using a random sample from the mixture distribution f(x)=∫f x | θ)g(θ)dθ where f(· | θ) is a known discrete exponen tial family of density functions. Recently two techniques for estimating g have been proposed. The first uses Fourier analysis and the method of kernels and the second uses orthogonal polynomials. It is known that the first technique is capable of yielding estimators that achieve (or almost achieve) the minimax convergence rate. We show that this is true for the technique based on orthogonal polynomials as well. The practical implementation of these estimators is also addressed. Computer experiments indicate that the kernel estimators give somewhat disappoint ing finite sample results. However, the orthogonal polynomial estimators appear to do much better. To improve on the finite sample performance of the orthogonal polynomial estimators, a way of estimating the optimal truncation parameter is proposed. The resultant estimators retain the convergence rates of the previous estimators and a Monte Carlo finite sample study reveals that they perform well relative to the ones based on the optimal truncation parameter.     

正交多项式回归模型参数估计的格子设计及其最小二乘估计

对二元二次多项式回归模型进行预先正交化处理，提出使用因子空间的N等份的格子设计的观点，推导出了信息矩阵的一般性结构，并给出了该设计的非退化条件及其最小二乘估计和对应的协方差矩阵。     

压铸机合模机构的正交回归优化设计

在对压铸机合模机构的优化设计中,采用正交回归设计法建立结构性能与设计变量的近似函数,对近似函数进行优化,从而有效地解决了结构优化设计过程中优化方法需要反复进行三维有限元分析而引起的超大计算量问题;这种方法对实际应用中大量存在而又无法得到解析式的结构优化问题有着普遍的意义。     

The Cox Proportional Hazards Model with a Partly Linear Relative Risk Function

The conventional Cox proportional hazards regression model contains a loglinear relative risk function, linking the covariate information to the hazard ratio with a finite number of parameters. A generalization, termed the partly linear Cox model, allows for both finite dimensional parameters and an infinite dimensional parameter in the relative risk function, providing a more robust specification of the relative risk function. In this work, a likelihood based inference procedure is developed for the finite dimensional parameters of the partly linear Cox model. To alleviate the problems associated with a likelihood approach in the presence of an infinite dimensional parameter, the relative risk is reparameterized such that the finite dimensional parameters of interest are orthogonal to the infinite dimensional parameter. Inference on the finite dimensional parameters is accomplished through maximization of the profile partial likelihood, profiling out the infinite dimensional nuisance parameter using a kernel function. The asymptotic distribution theory for the maximum profile partial likelihood estimate is established. It is determined that this estimate is asymptotically efficient; the orthogonal reparameterization enables employment of profile likelihood inference procedures without adjustment for estimation of the nuisance parameter. An example from a retrospective analysis in cancer demonstrates the methodology.     

Central limit theorems for four new types of U-designs

Orthogonal array (OA)-based Latin hypercube designs, also called U-designs, have been popularly adopted in designing a computer experiment. Nested U-designs, sliced U-designs, strong OA-based U-designs and correlation controlled U-designs are four types of extensions of U-designs for different applications in computer experiments. Their elaborate multi-layer structure or multi-dimensional uniformity, which makes them desirable for different applications, brings difficulty in analysing the related statistical properties. In this paper, we derive central limit theorems for these four types of designs by introducing a newly constructed discrete function. It is shown that the means of the four samples generated from these four types of designs asymptotically follow the same normal distribution. These results are useful in assessing the confidence intervals of the gross mean. Two examples are presented to illustrate the closeness of the simulated density plots to the corresponding normal distributions.     

仙人掌多糖口服液的研制

以ODPs为原料,采用正交试验确定口服液中关键成分的配比及制备工艺条件,并采用强光照射、高温、Rogers加温加速试验对口服液的稳定性进行研究.得出ODPs口服液的最佳灭菌条件为灭菌功率700W、灭菌时间9min;最佳处方（以1L口服液计）为ODPs 10g,甜菊糖0.64g,尼泊金混合酯0.025 6g,各项主要质量指标符合口服液制剂法定质量标准.ODPs口服液对光照不敏感,无需避光保存;高温试验、Rogers法测得ODPs口服液的t0.9为5.4h,说明在高温条件下,其稳定性较差,应低温储存.     

二级复合抛物面聚光器(CPC)性能仿真及光伏发电实验研究

构造出一个由2个复合抛物面聚光器(CPC)叠置组成的二级复合抛物面聚光器(CPC),为改善二级抛物面聚光器(CPC)的整体性能,对影响聚光器性能的3个关键参数,采用正交试验设计、方差分析和水平搭配的方法进行分析,并确定了二级CPC的优化结构形状。运用PRO-E建立二级CPC三维模型,并导入Tracepro软件进行性能仿真分析。用氙灯作为模拟太阳光源,对一组二级CPC模型装置进行了实验测试,仿真和实验的结果表明:二级CPC的结构形状为12°/35°~22°时,聚光器有效聚光比约为2.5,有效接收角为25°左右;由该聚光器构成的聚光光伏发电系统和太阳能非聚光光伏发电系统相比,功率积分值在夏至日提升了246%,春秋分提升了252%,冬至日提升了400%。     

Perturbation analysis for an orthogonal least-squares estimator

Coordinate measuring machines (CMMs) are used to check the geometric integrity of component parts. The geometric constraints to which a part must conform, as defined e.g., by The American National Standards Institute, assume the use of some type of gauging system when inspecting the part. Statistical issues arise in interpretting CMM data in the inspection of part tolerances. We consider a set of n planar regions on the surface of a part. The unit vector normal to each plane is estimated by orthogonal least squares. The small-sample density of this estimator (on the unit sphere S²) is determined asymptotically as the variance of the CMM error approaches 0. To a first-degree approximation, this density is Fisher-von Mises. Diagnostics are reviewed to test the geometric constraint that the n planar regions are oriented correctly with respect to one another, and to test the flatness of planar regions.