Fuzzy c-means clustering based on spatial neighborhood information for image segmentation

Fuzzy c-means （FCM） algorithm is one of the most popular methods for image segmentation. However, the standard FCM algorithm is sensitive to noise because of not taking into account the spatial information in the image. An improved FCM algorithm is proposed to improve the antinoise performance of FCM algorithm. The new algorithm is formulated by incorporating the spatial neighborhood information into the membership function for clustering. The distribution statistics of the neighborhood pixels and the prior probability are used to form a new membership func- tion. It is not only effective to remove the noise spots but also can reduce the misclassified pixels. Experimental results indicate that the proposed algorithm is more accurate and robust to noise than the standard FCM algorithm.

Ensemble Simulation of Land Evapotranspiration in China Based on a Multi-Forcing and Multi-Model Approach

In order to reduce the uncertainty of offline land surface model （LSM） simulations of land evapotranspiration （ET）, we used ensemble simulations based on three meteorological forcing datasets [Princeton, ITPCAS （Institute of Tibetan Plateau Research, Chinese Academy of Sciences）, Qian] and four LSMs （BATS, VIC, CLM3.0 and CLM3.5）, to explore the trends and spatiotemporal characteristics of ET, as well as the spatiotemporal pattern of ET in response to climate factors over China's Mainland during 1982-2007. The results showed that various simulations of each member and their arithmetic mean （EnsAVlean） could capture the spatial distribution and seasonal pattern of ET sufficiently well, where they exhibited more significant spatial and seasonal variation in the ET compared with observation-based ET estimates （Obs_MTE）. For the mean annual ET, we found that the BATS forced by Princeton forcing overestimated the annual mean ET compared with Obs_MTE for most of the basins in China, whereas the VIC forced by Princeton forcing showed underestimations. By contrast, the Ens_Mean was closer to Obs_MTE, although the results were underestimated over Southeast China. Furthermore, both the Obs_MTE and Ens_Mean exhibited a significant increasing trend during 1982-98; whereas after 1998, when the last big EI Nifio event occurred, the Ens_Mean tended to decrease significantly between 1999 and 2007, although the change was not significant for Obs_MTE. Changes in air temperature and shortwave radiation played key roles in the long-term variation in ET over the humid area of China, but precipitation mainly controlled the long-term variation in ET in arid and semi-arid areas of China.

Variable Selection of Partially Linear Single-index Models

In this article, we study the variable selection of partially linear single-index model(PLSIM). Based on the minimized average variance estimation, the variable selection of PLSIM is done by minimizing average variance with adaptive l1 penalty. Implementation algorithm is given. Under some regular conditions, we demonstrate the oracle properties of aLASSO procedure for PLSIM. Simulations are used to investigate the effectiveness of the proposed method for variable selection of PLSIM.

H_∞ Optimal Model Reduction for Singular Fast Subsystems

In this paper, H∞ optimal model reduction for singular fast subsystems will be inves-tigated. First, error system is established to measure the error magnitude between the original andreduced systems, and it is demonstrated that the new feature for model reduction of singular systemsis to make H∞ norm of the error system finite and minimal. The necessary and su?cient conditionis derived for the existence of the H∞ suboptimal model reduction problem. Next, we give an exactand practicable algorithm to get the parameters of the reduced subsystems by applying the matrixtheory. Meanwhile, the reduced system may be also impulsive. The advantages of the proposedalgorithm are that it is more ?exible in a straight-forward way without much extra computation, andthe order of the reduced systems is as minimal as possible. Finally, one illustrative example is givento illustrate the e?ectiveness of the proposed model reduction approach.

Modeling Cyber Loss Severity Using a Spliced Regression Distribution with Mixture Components

Cyber losses in terms of number of records breached under cyber incidents commonly feature a significant portion of zeros, specific characteristics of mid-range losses and large losses, which make it hard to model the whole range of the losses using a standard loss distribution. We tackle this modeling problem by proposing a three-component spliced regression model that can simultaneously model zeros, moderate and large losses and consider heterogeneous effects in mixture components. To apply our proposed model to Privacy Right Clearinghouse (PRC) data breach chronology, we segment geographical groups using unsupervised cluster analysis, and utilize a covariate-dependent probability to model zero losses, finite mixture distributions for moderate body and an extreme value distribution for large losses capturing the heavy-tailed nature of the loss data. Parameters and coefficients are estimated using the Expectation-Maximization (EM) algorithm. Combining with our frequency model (generalized linear mixed model) for data breaches, aggregate loss distributions are investigated and applications on cyber insurance pricing and risk management are discussed.

压水堆国产SA-508-Ⅲ-1钢环境影响疲劳试验研究和预测模型开发

对压水堆核电厂一回路设备用国产SA-508 Gr.3 Cl.1低合金钢(简称SA-508-Ⅲ-1钢)进行室温和320℃空气环境,以及模拟压水堆一回路水环境下的疲劳性能试验研究,获得国产SA-508-Ⅲ-1钢在空气环境下的疲劳寿命最佳拟合曲线(平均曲线)。在此基础上,对影响国产SA-508-Ⅲ-1钢在压水堆核电厂一回路水环境下疲劳性能的应变速率、温度和溶解氧含量等参数的影响规律进行研究,获得各影响参数的影响函数方程。基于获得的各影响参数的函数方程,建立国产SA-508-Ⅲ-1钢的环境影响疲劳修正因子F_(en)预测模型。本文获得的压水堆核电厂一回路水环境下国产SA-508-Ⅲ-1钢的疲劳寿命都位于95%置信度限值(10^(±2σ))范围内,验证了本文预测模型的有效性。同时,本文获得的压水堆核电厂一回路水环境下国产SA-508-Ⅲ-1钢的疲劳寿命与美国阿贡国家实验室(ANL)模型所预测的寿命相比,也都位于95%置信度限值(10^(±2σ))范围内,说明ANL模型可用于国产SA-508-Ⅲ-1钢的疲劳寿命预测。本文获得的国产SA-508-Ⅲ-1钢的环境影响疲劳预测模型与ANL模型相比,更适用于国产SA-508-Ⅲ-1钢的寿命预测,为国内第3代核电厂一回路设备考虑压水堆一回路水环境影响的疲劳设计提供参考。

Research on the effect estimation of seismic safety evaluation

Seismic safety evaluation is a basic work for determining the seismic resistance requirements of major construc-tion projects. The effect, especially the economic effect of the seismic safety evaluation has been generally con-cerned. The paper gives a model for estimating the effect of seismic safety evaluation and calculates roughly the economic effect of seismic safety evaluation with some examples.

Kinetics of Asymmetric Reduction of Phenylglyoxylic Acid to R-(-)-Mandelic Acid by Saccharomyces Cerevisiae FD11b

The kinetics of asymmetric production of R-（-）-mandelic acid （R-MA） from phenylglyoxylic acid （PGA） catalyzed by Saccharomyces cerevisiae sp. strain FD11b was studied by fed-batch cultures. The concentrations of glucose and PGA were controlled respectively with a dual feeding system. When the electron donor glucose was supplied at the rate of 0.0833mmol·gdw^-1·h^-1, the specific production rate （qp） and the enantiomeric excess of R-MA reached the maximum 0.353mmol·gdw^-1·h^-1 and 97.1%, respectively. The apparent reduction activity of yeast FD 11 b was obviously affected by both substrate PGA and product MA. The qp value reached the maximum 0.36-0.38mmol·gdw^-1·h^-1 when the PGA concentration was controlled between 25 and 35mmol·L^-1. The obvious substrate inhibition of bioconversion was observed at the PGA concentrations higher than 40mmol·L^-1. The accumulation of product MA also caused a severe feed-back inhibition for its production when the product concentration was above 60mmol·L^-1. The kinetic model with the inhibition effect of both substrate and product was simulated by a computer-based least-square arithrnatic. The established kinetic model was in good agreement with the experimental data.

Infinitesimal dividing modeling method for dual suppliers inventory model with random lead times

As one of the basic inventory cost models, the （Q, τ）inventory cost model of dual suppliers with random procurement lead time is mostly formulated by using the concepts of ＂effective lead time＂ and ＂lead time demand＂, which may lead to an imprecise inventory cost. Through the real-time statistic of the inventory quantities, this paper considers the precise （Q, τ） inventory cost model of dual supplier procurement by using an infinitesimal dividing method. The traditional modeling method of the inventory cost for dual supplier procurement includes complex procedures. To reduce the complexity effectively, the presented method investigates the statistics properties in real-time of the inventory quantities with the application of the infinitesimal dividing method. It is proved that the optimal holding and shortage costs of dual supplier procurement are less than those of single supplier procurement respectively. With the assumption that both suppliers have the same distribution of lead times, the convexity of the cost function per unit time is proved. So the optimal solution can be easily obtained by applying the classical convex optimization methods. The numerical examples are given to verify the main conclusions.

The Design and Control of Distillation Column with Side Reactors for Chlorobenzene Production

The distillation column with side reactors (SRC) can overcome the temperature/pressure mismatch in the traditional reactive distillation, the column operates at temperature/pressure favorable for vapor-liquid separation, while the reactors operate at temperatures/pressures favorable for reaction kinetics. According to the smooth operation and automatic control problem of the distillation column with side reactors (SRC), the design, simulation calculation and dynamic control of the SCR process for chlorobenzene production are discussed in the paper. Firstly, the mechanism models, the integrated structure optimal design and process simulation systems are established, respectively. And then multivariable control schemes are designed, the controllability of SRC process based on the optimal steady-state integrated structure is explored. The dynamic response performances of closed-loop system against several disturbances are discussed to verify the effectiveness of control schemes for the SRC process. The simulating results show that the control structure using conventional control strategies can effectively overcome feeding disturbances in a specific range.

ASSESSMENT OF LOCAL INFLUENCE IN MULTIVARIATE REGRESSION MODEL

In this article, authors introduce a method to assess local influence of obser- vations on the parameter estimates and prediction in multivariate regression model. The diagnostics under the perturbations of error variance, response variables and explanatory variables are derived, and the results are compared with those of case- deletion. Two examples are analyzed for illustration.

Combined model based on optimized multi-variable grey model and multiple linear regression

The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.

Arcing Model of a Disconnector and its Effect on VFTO

In the computational process of very fast transient over-voltage （VFTO）, it is essen-tial to find an accurate model for a gas insulated substation. The arcing model of the disconnector is particularly important. The general arcing model is not able to give a good description of the arc development process. In this paper, based on the physical process of arcing and existing arc models （the exponential time-varying resistance model and the segmental arcing models）, a dy- namic arcing model is proposed, which is divided into two stages before and after the zero crossing. The dynamic arcing model combines hyperbola time-varying resistance and the Mayr model to describe the dynamic process of arcing. The present paper creates an arc model blockset upon the Matlab/Simulink software platform. Moreover for a specific 1100 kV station, VFTO is simulated in detail based on different arcing models. It is demonstrated that the dynamic arcing model can describe the physical arc process precisely and is useful for improving the accuracy of VFTO simulations.

Statistical Modeling Studies of Iron Recovery from Red Mud Using Thermal Plasma

Optimization studies of plasma smelting of red mud were carried out. Reduction of the dried red mud fines was done in an extended arc plasma reactor to recover the pig iron. Lime grit and low ash metallurgical （LAM） coke were used as the flux and reductant, respectively. 2level factorial design was used to study the influence of all parameters on the responses. Response surface modeling was done with the data obtained from statistically designed experiments. Metal recovery at optimum parameters was found to be 79.52%.

A Novel Verification Approach of Workflow Schema

A workflow schema is an abstract description of the business processed by workflow model, and plays a critical role in analyzing, executing and reorganizing business processes. The verification issue on the correctness of complicated workflow schemas is difficult in the field of workflow. We make an intensive study of it in this paper. We present here local errors and schema logic errors （global errors） in workflow schemas in detail, and offer some constraint rules trying to avoid schema errors during modeling. In addition, we propose a verification approach based on graph reduction and graph spread, and give the algorithm. The algorithm is implemented in a workflow prototype system e-ScopeWork.

Research of Privacy Preservation Method Based on Data Coloring

In the cloud computing environment, outsourcing service mode of data storage causes the security problem, the reliability of data cannot be guaranteed, and the privacy preservation problem has aroused wide concern. In order to solve the problem of inefficiency and high-complexity caused by traditional privacy preservation methods such as data encryption and access control technology, a privacy preservation method based on data coloring is proposed. The data coloring model is established and the coloring mechanism is adopted to deal with the sensitive data of numerical attributes, and the cloud model similarity measurement based on arithmetic average least-approximability is adopted to authenticate the ownership of privacy data. On the premise of high availability of data, the method strengthens the security of the privacy information. Then, the performance, validity and the parameter errors of the algorithm are quantitatively analyzed by the experiments using the UCI dataset. Under the same conditions of privacy preservation requirements, the proposed method can track privacy leakage efficiently and reduce privacy leakage risks. Compared with the k-anonymity approach, the proposed method enhances the computational time efficiency by 18.5%.

Simple analytical model for depth-averaged velocity in meandering compound channels

A simple but applicable analytical model is presented to predict the lat- eral distribution of the depth-averaged velocity in meandering compound channels. The governing equation with curvilinear coordinates is derived from the momentum equation and the flow continuity equation under the condition of quasi-uniform flow. A series of experiments are conducted in a large-scale meandering compound channel. Based on the experimental data, a magnitude analysis is carried out for the governing equation, and two lower-order shear stress terms are ignored. Four groups of experimental data from different sources are used to verify the predictive capability of this model, and good predictions are obtained. Finally, the determination of the velocity parameter and the limitation of this model are discussed.

Modeling of Diffusion Transport through Oral Biofilms with the Inverse Problem Method

Aim The purpose of this study was to develop a mathe-matical model to quantitatively describe the passive trans-port of macromolecules within dental biofilms. Methodology Fluorescently labeled dextrans with different molecular mass （3 kD,10 kD,40 kD,70 kD,2 000 kD） were used as a series of diffusion probes. Streptococcus mutans,Streptococcus sanguinis,Actinomyces naeslundii and Fusobacterium nucleatum were used as inocula for biofilm formation. The diffusion processes of different probes through the in vitro biofilm were recorded with a confocal laser microscope. Results Mathematical function of biofilm penetration was constructed on the basis of the inverse problem method. Based on this function,not only the relationship between average concentration of steady-state and molecule weights can be analyzed,but also that between penetrative time and molecule weights. Conclusion This can be used to predict the effective concentration and the penetrative time of anti-biofilm medicines that can diffuse through oral biofilm. Further-more,an improved model for large molecule is proposed by considering the exchange time at the upper boundary of the dental biofilm.

Statistical Relationship Between UVB(280-320nm) and Broadband Solar Radiation(295-2800nm) at a Subtropical Location(Qena,Egypt)

The present study quantifies the relationship between ultraviolet-B(UVB) and broadband solar radiation(G) at Qena,Egypt.Data from 10-year hourly integrated totals for both UVB and G on a horizontal surface were used to determine the best fit between the two radiation types.On the basis of the correlation of determination(r2),a second-order polynomial was determined to provide the best fit.For the purpose of developing an empirical model to estimate UVB,all of the cases of UVB and G from a nine-year study from 2001 to 2009 were introduced.Monthly and seasonal empirical models,as well as a general expression,were established for UVB as a function of G.The values of r2 ranged from 0.90 to 0.97.By using a new dataset of G,the estimated and the corresponding measured values of UVB were determined to be in good agreement whereby the values of r2 between the two ranged from 0.91 to 0.98.In addition,the significance and performance of the regression forms were evaluated with the aid of several statistical analysis procedures.The values of the index of modeling(d) and coefficient of modeling efficiency(ME) were close to one.Moreover,the values of RMSE,mean bias error(MBE),and mean absolute error(MAE) were lower than the experimental errors.On the basis of this analysis,it has been determined that the suggested regression forms can be used to estimate UVB when it difficult to obtain measurements or when measurements are available only for limited periods at the studied region.

Exact solutions of nonlinear fractional differential equations by (G'/G)-expansion method

In this paper, we use the fractional complex transform and the （G＇/G）-expansion method to study the nonlinear fractional differential equations and find the exact solutions. The fractional complex transform is proposed to convert a partial fractional differential equation with Jumarie＇s modified Riemann-Liouville derivative into its ordinary differential equation. It is shown that the considered transform and method are very efficient and powerful in solving wide classes of nonlinear fractional order equations.