DIFFERENTIAL GEOMETRICAL METHODS IN THE STUDY OF OPTICAL-TRANSMISSION (SCALAR THEORY) .2. TIME-DEPENDENT TRANSMISSION THEORY

By generalization of the methods presented in Part I of the study [J. Opt. Soc. Am. A 12, 600 (1994)] to the four-dimensional (4D) Riemannian manifold case, the time-dependent behavior of light transmitting in a medium is investigated theoretically by the geodesic equation and curvature in a 4D manifold. In addition, the field equation is restudied, and the 4D conserved current of the optical fluid and its conservation equation are derived and applied to deduce the time-dependent general refractive index. On this basis the forces acting on the fluid are dynamically analyzed and the self-consistency analysis is given.

Beam conditions for radiation generated by an electromagnetic J 0-correlated Schell-model source

Based on the 2 x 2 (electric field) cross-spectral density matrix, a model for an electromagnetic J(0)-correlated Schell-model beam is given that is a generalization of the scalar J(0)-correlated Schell-model beam. The conditions that the matrix for the source to generate an electromagnetic J(0)-correlated Schell-model beam are obtained. The condition for the source to generate a scalar J(0)-correlated Schell-model beam can be considered as a special case. (C) 2008 Optical Society of America

小波分析和人工神经网络在生态学研究中的应用

墨西哥帽子小波和Morlet小波在生态格局分析中的应用 本研究采用Monte Carlo方法，探讨了对小波分析的格局进行统计显著性检验的普遍方法。为了更好利用小波分析和了解两个常用小波--墨西哥帽子小波和Morlet小波在格局分析中的优缺点，用生态学研究中常见的4个模拟格局和东灵山辽东栎林的样带数据对这两个常用小波的特性进行了分析和比较。研究结果表明：墨西哥帽子小波能较好地分析样带中的斑块和间隙以及它们的位置信息，Morlet小波能较好地分析样带中尺度及其位置信息。不同的小波通常在尺度分析和斑块和间隙分析之间有平衡，所以最好的方法是结合两种小波的优点。小波分析在处理生态数据时，受所使用小波本身特性的制约。用墨西哥帽子小波进行格局分析时，小波能量谱的等值图上不同格局所对应的峰有可能相互重叠，当所分析的多尺度格局的规模差别不大时，所分析格局规模所对应的峰可能相互融合。这些小波能量谱的等值图上不同格局所对应峰的重叠和融合可能会导致格局分析量图上多个峰的相互融合和屏蔽。所以在使用小波分析做格局研究时，也应尽可能地结合小波能量谱和量图上的信息，以得到较全面和精确的格局分析信息。本研究的结论能为小波分析的应用提供指导。 应用二维小波分析对暖温带阔叶林辽东栎更新格局的研究 本研究介绍了一种二维网格空间数据分析方法一二维小波分析。该方法不仅能分析格局的等级结构，而且也能得到所分析结构的位置信息。小波系数等值图上不同格局规模的斑块和间隙可直接和不同尺度上的生态过程和生境条件相联系。小波方差从二维小波分析导出，小波方差可将四维的小波系数降至二维的小波方差函数，并量化所分析格局规模对整个格局的贡献。本研究用三个模拟格局分析了二维小波的特性及二维墨西哥帽子小波和Halo小波的特性。因为自身的特性，Halo小波比墨西哥帽子小波能提供更高的分辨率。本研究也将二维小波分析应用于暖温带阔叶林的辽东栎更新格局研究中，分析的结果表明：辽东栎的更新发生在辽东栎成树斑块和林窗斑块重叠区域。 用交互验证和独立验证来测试神人工经网络模拟水稻分檗动态的泛化能力 人工神经网络不是基于对所模拟过程的理解，而是依赖于对所分析数据的内部结构。所以人工神经网络通常被认为是经验模型而不能外推，而且在训练数据和验证数据的范围之外肯定不能精确地预测所模拟的过程。本研究通过对交互验证和独立验证神经网络模型性能的比较，测试了神经网络模型在预测水稻分檗动态方面的泛化能力。同时，也对几种提高神经网络泛化能力的技术进行了比较。研究结果表明：在训练数据的变量范围内，神经网络在预测水稻分檗动态方面具有泛化能力。较少的训练数据样本导致了对训练数据过度吻合的和不具泛化能力的神经网络。要能使神经网络在预测水稻分檗动态方面具有泛化能力，训练数据的样本量至少9倍于神经网络的权值数目。当神经网络有多个输入变量且训练数据不足以保证神经网络的泛化能力时，建议在训练之前，采用主成分分析、对应分析及类似技术压缩输入变量的个数。在压缩输入变量的个数之后，如果训练数据的样本量还不足以保证神经网络的泛化能力，就应采用提高神经网络泛化能力的技木，如：jittering和强制训练停止等，特别是神经网络与机理模型的复合模型。因为神经网络的泛化能力问题具有普遍性，所以我们的研究结论不只是适用于水稻分檗动态的预测，也适用于其它的农业和生态神经网络模型。

Nutrient dynamics and the eutrophication of shallow lakes Kasumigaura (Japan), Donghu (PR China), and Okeechobee (USA)

We compared the nutrient dynamics of three lakes that have been heavily influenced by point and non-point source pollution and other human activities. The lakes, located in Japan (Lake Kasumigaura), People's Republic of China (Lake Donghu), and the USA (Lake Okeechobee), all are relatively large(>30 km(2)), very shallow (<4 m mean depth), and eutrophic. In all three lakes we found strong interactions among the sediments, water column, and human activities. Important processes affecting nutrient dynamics included nitrogen fixation, light limitation due to resuspended sediments, and intense grazing on algae by cultured fish. As a result of these complex interactions, simple empirical models developed to predict in-lake responses of total phosphorus and algal biomass to external nutrient loads must be used with caution. While published models may provide 'good' results, in terms of model output matching actual data, this may not be due to accurate representation of lake processes in the models. The variable nutrient dynamics that we observed among the three study lakes appears to be typical for shallow lake systems. This indicates that a greater reliance on lake-specific research may be required for effective management, and a lesser role of inter-lake generalization than is possible for deeper, dimictic lake systems. Furthermore, accurate predictions of management impacts in shallow eutrophic lakes may require the use of relatively complex deterministic modeling tools. (C) 2000 Elsevier Science Ltd. All rights reserved.

Biomimetic pattern recognition theory and its applications

Biomimetic pattern recogntion (BPR), which is based on "cognition" instead of "classification", is much closer to the function of human being. The basis of BPR is the Principle of homology-continuity (PHC), which means the difference between two samples of the same class must be gradually changed. The aim of BPR is to find an optimal covering in the feature space, which emphasizes the "similarity" among homologous group members, rather than "division" in traditional pattern recognition. Some applications of BPR are surveyed, in which the results of BPR are much better than the results of Support Vector Machine. A novel neuron model, Hyper sausage neuron (HSN), is shown as a kind of covering units in BPR. The mathematical description of HSN is given and the 2-dimensional discriminant boundary of HSN is shown. In two special cases, in which samples are distributed in a line segment and a circle, both the HSN networks and RBF networks are used for covering. The results show that HSN networks act better than RBF networks in generalization, especially for small sample set, which are consonant with the results of the applications of BPR. And a brief explanation of the HSN networks' advantages in covering general distributed samples is also given.

Method for improving classification performance of neural network based on fuzzy input and network inversion

In order to effectively improve the classification performance of neural network, first architecture of fuzzy neural network with fuzzy input was proposed. Next a cost function of fuzzy outputs and non-fuzzy targets was defined. Then a learning algorithm from the cost function for adjusting weights was derived. And then the fuzzy neural network was inversed and fuzzified inversion algorithm was proposed. Finally, computer simulations on real-world pattern classification problems examine the effectives of the proposed approach. The experiment results show that the proposed approach has the merits of high learning efficiency, high classification accuracy and high generalization capability.

Chiral symmetry analysis and rigid rotational invariance for the lattice dynamics of single-wall carbon nanotubes

We provide a detailed expression of the vibrational potential for the lattice dynamics of single-wall carbon nanotubes (SWCNT's) satisfying the requirements of the exact rigid translational as well as rotational symmetries, which is a nontrivial generalization of the valence force model for the planar graphene sheet. With the model, the low-frequency behavior of the dispersion of the acoustic modes as well as the flexure mode can be precisely calculated. Based upon a comprehensive chiral symmetry analysis, the calculated mode frequencies (including all the Raman- and infrared-active modes), velocities of acoustic modes, and the polarization vectors are systematically fitted in terms of the chiral angle and radius, where the restrictions of various symmetry operations of SWCNT's are fulfilled.

Practical Evaluation of Security against Generalized Interpolation Attack

Interpolation attack was presented by Jakobsen and Knudsen at FSE'97. Interpolation attack is effective against ciphers that have a certain algebraic structure like the PURE cipher which is a prototype cipher, but it is difficult to apply the attack to real-world ciphers. This difficulty is due to the difficulty of deriving a low degree polynomial relation between ciphertexts and plaintexts. In other words, it is difficult to evaluate the security against interpolation attack. This paper generalizes the interpolation attack. The generalization makes easier to evaluate the security against interpolation attack. We call the generalized interpolation attack linear sum attack. We present an algorithm that evaluates the security of byte-oriented ciphers against linear sum attack. Moreover, we show the relationship between linear sum attack and higher order differential attack. In addition, we show the security of CRYPTON, E2, and RIJNDAEL against linear sum attack using the algorithm.

On equations for regular languages, finite automata, and sequential networks

We consider systems of equations of the form where A is the underlying alphabet, the Xi are variables, the Pi,a are boolean functions in the variables Xi, and each δi is either the empty word or the empty set. The symbols υ and denote concatenation and union of languages over A. We show that any such system has a unique solution which, moreover, is regular. These equations correspond to a type of automation, called boolean automation, which is a generalization of a nondeterministic automation. The equations are then used to determine the language accepted by a sequential network; they are obtainable directly from the network.

内循环流化床生物质气化过程的神经网络模型

基于BP人工神经网络原理，利用MATLAB神经网络工具箱，以实验得到的57组气化实验数据作为样本，建立了一个以加料量和送风量为输入变量，以燃气热值、产气率、碳转化率和气化效率为输出变量，用于描述连续稳定气化过程的内循环流化床生物质气化模型。对模型的隐层节点数和训练周期改变对模拟结果的影响进行了分析，发现当隐层节点数为20，训练步骤为50步，模型的4个输出变量的模拟结果与实验结果相关系数均超过0．95；同时对该模型的预测能力进行了考察，模型预测结果与实验结果吻合良好，证明了该模型具有较强的泛化能力，为生物质内循环流化床气化系统的优化设计和自动控制提供新思路。

基于滤波方法的DEM尺度变换方法研究

针对水土流失评价中地形因子的尺度效应问题,引入数字图像处理中的滤波分析方法,对5 m分辨率DEM进行了滤波处理,并通过地形综合特征分析,坡度、曲率制图统计分析,派生等高线与河流提取统计分析等方法,对滤波处理的综合效果进行了分析论证。结果表明,利用滤波方法可以实现对高分辨率DEM的综合,利用比例尺因子为5或者10的处理,其结果与10 m分辨率DEM或1∶5万地形图在反映地形起伏方面相似。

固液黏着功的Berthelot平均规则的推广及应用

以固液黏着功的Berthelot几何平均规则及其推广为基础的Zisman方程、Fowkes方程和Owens-Wendt方程是固体表面张力测定的基础.对Berthelot几何平均规则进行了进一步的推广,并以此为基础,对Zisman方程中的参数给出了推广的表示式,并对Fowkes方程和Owens-Wendt方程进行了进一步的推广.

Energy-Momentum of a Cosmological Brane Model and the Gauge Hierarchy

We analyze in this paper the general covariant energy-momentum tensor of the gravitational system in general five-dimensional cosmological brane-world models. Then through calculating this energy-momentum for the cosmological generalization of the Randall-Sundrum model, which includes the original RS model as the static limit, we are able to show that the weakness of the gravitation on the "visible" brane is a general feature of this model. This is the origin of the gauge hierarchy from a gravitational point of view. Our results are also consistent with the fact that a gravitational system has vanishing total energy.

The influence of bond valence on bond covalency in RMn2O5 (R=La, Pr, Nd, Sm, Eu)

The relationship between bond valence and bond covalency in RMn2O5 (R = La, Pr, Nd, Sm, Eu) has been investigated by a semiempirical method. This method is the generalization of the dielectric description theory of Phillips, Van Vechten, Levine and Tanaka scheme. The results indicate that larger valences usually result in higher bond covalencies, in good agreement with the point that the excess charge in the bonding region is the origin of formation of bond covalency. Other factors, such as oxidation state of elements, only make a small contribution to bond covalency.

Bond covalencies in R2BaCuO5 (R = Sm, Gd, Dy, Ho, Y, Er, Tm, Yb, Lu)

Bond covalencies in R2BaCuO5 (R = Sm, Gd, Dy, Ho, Y, Er, Tm, Yb, Lu) were calculated by means of a semiempirical method. This method is the generalization of the dielectric description theory of Phillips-Van Vechten-Levine-Tanaka scheme. The present paper presents the formula concerning the decomposing of complex crystals which are usually anisotropic systems into the sum of binary crystals which are isotropic systems. It can be seen that although the bond covalency is related to many physical quantities, it is mainly influenced by bond valence or bond charge, and a higher bond valence will produce higher bond covalency.