指定类数下仿射传播聚类的快速算法

针对Science杂志上提出的仿射传播(Affinity propagation)聚类产生指定类数的聚类结果时效率较低的问题,提出了基于多网格策略的快速算法。该算法采用多网格搜索策略来减少调用仿射传播算法的次数,改进偏向参数的上界以缩小搜索范围。新方法大幅度地提高了仿射传播聚类在指定类数下的速度性能。实验结果表明新方法十分有效,在运行时间上比现有方法减少了22%-90%。

三谈氧化数

首先对国内化学教材在描述氧化数概念时存在的不同说法进行讨论,在此基础上建议用指定电荷数一词代替形式电荷数(或形式荷电数)和表观电荷数来描述氧化数,然后通过解读氧化数的定义,得出若干重要推论,最后介绍了我们在编写无机化学教材时对氧化数部分内容所进行的探索与尝试,并建议在无机化学、普通化学教材中引入确定元素氧化数的价层电子数法。

An Entropy-based Index for Fine-scale Mapping of Disease Genes

By comparing the entropy and the conditional entropy in a marker, an entropy-based index has been presented for fine-scale linkage disequilibrium gene mapping using high-density marker maps for human disease genes. The index can quantify the level of linkage disequilibrium （LD） between the marker and the disease susceptibility locus （DSL） of genes. The advantage of using the index is attributed to the fact that it does not depend on marker allele frequencies across loci. Moreover, it is parallel to Hardy-Weinberg disequilibrium （HWD） measure for DSL fine mapping. Through various simulations, the fine mapping perform- ances of the proposed entropy-based index was extensively investigated under various genetic parameters. The results show that the index presented is both robust and powerful for DSL mapping in genes.

A non-parametric indicator Kriging method for generating coastal sediment type map

Coastal sediment type map has been widely used in marine economic and engineering activities, but the traditional mapping methods had some limitations due to their intrinsic assumption or subjectivity. In this paper, a non-parametric indicator Kriging method has been proposed for generating coastal sediment map. The method can effectively avoid mapping subjectivity, has no special requirements for the sample data to meet second-order stationary or normal distribution, and can also provide useful information on the quantitative evaluation of mapping uncertainty. The application of the method in the southern sea area of Lianyungang showed that much more convincing mapping results could be obtained compared with the traditional methods such as IDW, Kriging and Voronoi diagram under the same condition, so the proposed method was applicable with great utilization value.

Stabilization of discrete nonholonomic chained system

Aimed at the stabilization of the nonholonomic chained system under fixed sample control, two control laws were proposed. The discrete model of the nonholonomic chained system under zero-hold was obtained through the integrate method to the continuous model. And the discrete model was transformed to the form with two linear subsystems through coordinate transformation. Two feedback control laws, time-invariant control law and time-varying control law, were proposed; and the local stabilization and global stabilization were realized respectively. The simulation results show the effectiveness of the proposed control laws. The discrete nonholonomic chained system can converge to zero from any initial state exponentially, and the convergence rate can be changed through changing the parameters of the control laws.

摺呈收遣难民办法

(一)由省政府就鄂西、鄂北、鄂南等处各指定数县,广设难民收容所,至少共须能容十五万人,其各县收容名额由省府支配.(二)前项指定各县收容在[之]经费除由各该县自筹外,不足之数,由非常时期难民救济委员会各县支会呈请省府拨补.

什么是期货市场

商品交易所是买方卖方进行期货合约买卖的场所,期货合约是一项在将来指定日期买进或卖出某种指定数量和品质商品的协议。买卖的期货合约必须在交易所内经过公开竞争的形式进行,这种交易所称为期货市场。大多数期货合约在未满期前便“对冲”了(或称“平仓”),即自己所持的期货合约先卖后买,否则就必须依据合约进行现货交割;一般进行现货交割的期货合约只占总数的3％至10％左右。商品交易所本身并不进行商品买卖活动,只为生产者、经营者、加工商、出口商和投机者提供进行期货合约买卖的场所,并负起监督的任务。

世界上著名的期货市场

商品交易所是买方和卖方进行期货合约买卖的场所。期货合约是一项在将来指定日期,买进或卖出某种指定数量和品质商品的协议,即买方同意在将来指定的价格,向卖方收取某种商品;而卖方也同意在将来指定的日期,交出某种商品,以换取合约规定的价格。买卖的期货合约,必须在交易所内经过公开竞争的形式进行。

Absolute Exponential Stability of Generalized Dynamical Neural Networks

This paper investigates the absolute exponential stability of generalized neural networks with a general class of partially Lipschitz continuous and monotone increasing activation functions. The main obtained result is that if the interconnection matrix T of the neural system satisfies that - T is an H matrix with nonnegative diagonal elements, then the neural system is absolutely exponentially stable(AEST). The Hopfield network, Cellular neural network and Bidirectional associative memory network are special cases of the network model considered in this paper. So this work gives some improvements to the previous ones.

Coherence of wind pressure on domes

The concept of the coherence function is adopted to find the wind pressure correlation of two points on domes of different rise-span ratios. The pressure measurements are made on the dome roof models by the wind tunnel test. The coherence functions for different separation distances at several directions of the domes from different wind directions are examined. The results show that there is a strong correlation for two adjacent points at low frequency, but not for non-adjacent points. The coherence of the wind pressure increases with the decrease in the separation distance. Moreover, the coherence of the wind pressure is in the strongest correlation on the along-wind direction at the same separation, but the lowest correlation is on the cross-wind direction. The detailed derivation of the proposed exponential coherence model of the wind pressure from experimental data is also discussed. It is found that the proposed exponential coherence model can be appropriate, especially, for small separations and the change in the directions on domes. Based on the quasi-steady theory, the relationship between the wind pressure and the wind velocity on the basis of the coherence model is also examined. The coherence observed between the wind pressure and the wind velocity is not adequately predicted by the quasi-steady theory.

Exponential Stability of Large-Scale Non-Linear Systems with Multiple The Delays

The problem of stabilizing a class of large-scale non-linear multiple delay systems is considered.The complicated system is decomposed into several subsystems; each function of them is expressed by a set of components of the overall state vector,with interconnections between them, and the subsystems are coupled by the delayed state. In this paper, a method is devised to be a suitable choice of state feedback controls of every subsystems, moreover, it is proved that the large-scale system is exponential stable.

Exponential stabilization of distributed parameter switched systems under dwell time constraints

The exponential stabilization problem for finite dimensional switched systems is extended to the infinite dimensional distributed parameter systems in the Hilbert space. Based on the semigroup theory, by applying the multiple Lyapunov function method, the exponential stabilization conditions are derived. These conditions are given in the form of linear operator inequalities where the decision variables are operators in the Hilbert space; while the stabilization properties depend on the switching rule. Being applied to the two-dimensional heat switched propagation equations with the Dirichlet boundary conditions, these linear operator inequalities are transformed into standard linear matrix inequalities. Finally, two examples are given to illustrate the effectiveness of the proposed results.

Robust exponential stability analysis of a larger class of discrete-time recurrent neural networks

The robust exponential stability of a larger class of discrete-time recurrent neural networks (RNNs) is explored in this paper. A novel neural network model, named standard neural network model (SNNM), is introduced to provide a general framework for stability analysis of RNNs. Most of the existing RNNs can be transformed into SNNMs to be analyzed in a unified way. Applying Lyapunov stability theory method and S-Procedure technique, two useful criteria of robust exponential stability for the discrete-time SNNMs are derived. The conditions presented are formulated as linear matrix inequalities (LMIs) to be easily solved using existing efficient convex optimization techniques. An example is presented to demonstrate the transformation procedure and the effectiveness of the results.

Allometric equations for estimating leaf area index(LAI) of two important tropical species(Tectona grandis and Dendrocalamus strictus)

Leaf area index（LAI） of Teak（Tectona grandis） and Bamboo（Dendrocalamus strictus） grown in Shoolpaneshwar Wildlife Sanctuary of Narmada District,Gujarat,India was obtained by destructive sampling,photo-grid method and by litter trap method.An allometric equation（between leaf area by litter trap method and canopy spread area） was developed for the determination of LAI.Results show that LAI value calculated by the developed allometric equation was similar to that estimated by destructive sampling and photo-grid method,with Root Mean Square Error（RMSE） of 0.90 and 1.15 for Teak,and 0.38 and 0.46 for Bamboo,respectively.There was a perfect match in both the LAI values（estimated and calculated）,indicating the accuracy of the developed equations for both the species.In conclusion,canopy spread is a better and sensitive parameter to estimate leaf area of trees.The developed equations can be used for estimating LAI of Teak and Bamboo in tropics.

Stability Analysis of Cohen-Grossberg Neural Networks with Time-Varying Delays

The global exponential stability of Cohen-Grossberg neural networks with time-varying delays is studied. By constructing several suitable Lyapunov functionals and utilizing differential in-equality techniques, some sufficient criteria for the global exponential stability and the exponential convergence rate of the equilibrium point of the system are obtained. The criteria do not require the activation functions to be differentiable or monotone nondecreasing. Some stability results from previous works are extended and improved. Comparisons are made to demonstrate the advantage of our results.

A Quantitative Structure Property Relationship for Prediction of Flash Point of Alkanes Using Molecular Connectivity Indices

Many structure-property/activity studies use graph theoretical indices, which are based on the topological properties of a molecule viewed as a graph. Since topological indices can be derived directly from the molecular structure without any experimental effort, they provide a simple and straightforward method for property prediction. In this work the flash point of alkanes was modeled by a set of molecular connectivity indices （Х）, modified molecular connectivity indices （ ^mХ^v ） and valance molecular connectivity indices （ ^mХ^v ）, with ^mХ^v calculated using the hydrogen perturbation. A stepwise Multiple Linear Regression （MLR） method was used to select the best indices. The predicted flash points are in good agreement with the experimental data, with the average absolute deviation 4.3 K.

On exponential stability for systems with state delays

This paper considers the issue of delay-dependent exponential stability for time-delay systems. Both nominal and uncertain systems are investigated. New sufficient conditions in terms of linear matrix inequalities(LMIs) are obtained. These criteria are simple owing to the use of an integral inequality. The model transformation approaches,bounding techniques for cross terms and slack matrices are all avoided in the derivation. Rigorous proof and numerical examples showed that the proposed criteria and those based on introducing slack matrices are equivalent.

Exponential stability for networked control systems based on the model of nonlinear discrete-time system with time-varying delay

An uncertain nonlinear discrete-time system model with time-varying input delays for networked control systems (NCSs) is presented. The problem of exponential stability for the system is considered and some new criteria of exponential stability are obtained based on norm inequality methods. A numerical example is given todemonstrate that those criteria are useful to analyzing the stability of nonlinear NCSs.

Contributions to Hom-Schunck optical flow equations-part I： Stability and rate of convergence of classical algorithm

Globally exponential stability （which implies convergence and uniqueness） of their classical iterative algorithm is established using methods of heat equations and energy integral after embedding the discrete iteration into a continuous flow. The stability condition depends explicitly on smoothness of the image sequence, size of image domain, value of the regularization parameter, and finally discretization step. Specifically, as the discretization step approaches to zero, stability holds unconditionally. The analysis also clarifies relations among the iterative algorithm, the original variation formulation and the PDE system. The proper regularity of solution and natural images is briefly surveyed and discussed. Experimental results validate the theoretical claims both on convergence and exponential stability.

Application of uncertainty reasoning based on cloud model in time series prediction

Time series prediction has been successfully used in several application areas, such as meteoro-logical forecasting, market prediction, network traffic forecasting, etc. , and a number of techniques have been developed for modeling and predicting time series. In the traditional exponential smoothing method, a fixed weight is assigned to data history, and the trend changes of time series are ignored. In this paper, an uncertainty reasoning method, based on cloud model, is employed in time series prediction, which uses cloud logic controller to adjust the smoothing coefficient of the simple exponential smoothing method dynamically to fit the current trend of the time series. The validity of this solution was proved by experiments on various data sets.