R/S AND WAVELET ANALYSIS ON EVOLUTIONARYPROCESS OF REGIONAL ECONOMIC DISPARITY IN CHINA DURING PAST 50 YEARS

This paper shows the dynamic process of regional disparity of economic development in China in the past 50 years from a new insight by using the rescaled range statistic (R/S) analysis and wavelet analysis of the Theil index sequence with different time scales. The main conclusions are: 1) The regional disparity of economic development in China, including the inter-provincial disparity, inter-regional disparity and intra-regional disparity, has existed for many years. Theil index by the comparative price has revealed the true trend for comparative disparity of regional economic development from 1952 to 2000. 2) Decomposition of Theil index indicates that the dynamic trend of comparative inter-provincial disparity in the coastal region is in line with dynamic trend of inter-provincial disparity in the whole China. 3) The R/S analysis results tell us that during 1966-1978, the Hurst exponent H=0.504 approximate to 0.5, which indicates that in that period the evolution of comparative inter-provincial disparity of economic development showed a random characteristic, and in the other periods, i.e. 1952-1965, 1979-1990 and 1991-2000, the Hurst exponent H>0.5, which indicates that in those periods the evolution of the comparative inter-provincial disparity of economic development in China had a long-enduring characteristic. 4) By using wavelet analysis at different time scale, we arrived at a conclusion that the evolutionary process of the disparity of economic development of China is not a simple inverted U shape but a compound of several U shapes. The result tells us that the evolutionary plot of inter-provincial disparity in China follows the inverted U on the whole at the higher scale, 24 ( 16 years). That is to say, the disparity tends to rise in the first stage of economic development, and fall slowly over the peak in the second stage of economic development. However, if we shorten the time scale to 23 ( 8 years), then a link of several U shapes will appear.

A Non-inferiority Trial Design without Need for a Conventional Margin

The NI （non-inferiority） trial design based on the likelihood ratio test eliminates the dependency on the conventional NI margin, and it explicitly uses the MCID （minimum clinical important difference） that links the statistical analysis to the clinical sense. Different from the conventional trial design, the new methodology is self-adaptive to the change in the sample size and overall cure rate, and it has an asymptotic property. It is shown that MCID is de-composite into constant MCID and statistical MCID. Along with this concept, the concept of the allowed inferiority does not exist, the interpretation of the trial result is more accurate and consistent to the statistical theory as well as the clinical interpretations.

Analysis of color distortion and optimum fusion for remote sensing images using the statistical property of wavelet decomposition

IHS （Intensity, Hue and Saturation） transform is one of the most commonly used tusion algonthm. But the matching error causes spectral distortion and degradation in processing of image fusion with IHS method. A study on IHS fusion indicates that the color distortion can＇t be avoided. Meanwhile, the statistical property of wavelet coefficient with wavelet decomposition reflects those significant features, such as edges, lines and regions. So, a united optimal fusion method, which uses the statistical property and IHS transform on pixel and feature levels, is proposed. That is, the high frequency of intensity component Ⅰ is fused on feature level with multi-resolution wavelet in IHS space. And the low frequency of intensity component Ⅰ is fused on pixel level with optimal weight coefficients. Spectral information and spatial resolution are two performance indexes of optimal weight coefficients. Experiment results with QuickBird data of Shanghai show that it is a practical and effective method.

Improved Kernel PLS-based Fault Detection Approach for Nonlinear Chemical Processes

In this paper, an improved nonlinear process fault detection method is proposed based on modified kernel partial least squares(KPLS). By integrating the statistical local approach(SLA) into the KPLS framework, two new statistics are established to monitor changes in the underlying model. The new modeling strategy can avoid the Gaussian distribution assumption of KPLS. Besides, advantage of the proposed method is that the kernel latent variables can be obtained directly through the eigen value decomposition instead of the iterative calculation, which can improve the computing speed. The new method is applied to fault detection in the simulation benchmark of the Tennessee Eastman process. The simulation results show superiority on detection sensitivity and accuracy in comparison to KPLS monitoring.

Transceiver Optimization for Multi-Antenna Device-to-Device Communications

It has been shown that the deployment of device-to-device(D2D) communication in cellular systems can provide better support for local services. However, improper design of the hybrid system may cause severe interference between cellular and D2D links. In this paper, we consider transceiver design for the system employing multiple antennas to mitigate the interference. The precoder and decoder matrices are optimized in terms of sum mean squared error(MSE) and capacity, respectively. For the MSE minimization problem, we present an alternative transceiver optimization algorithm. While for the non-convex capacity maximization problem, we decompose the primal problem into a sequence of standard convex quadratic programs for efficient optimization. The evaluation of our proposed algorithms for performance enhancement of the entire D2D integrated cellular system is carried out through simulations.

Assessment of Model Predictive Control Performance Criteria

The current highly competitive environment has driven industries to operate with increasingly restricted profit margins. Thus, it is imperative to optimize production processes. Faced with this scenario, multivariable predictive control of processes has been presented as a powerful alternative to achieve these goals. Moreover, the rationale for implementation of advanced control and subsequent analysis of its post-match performance also focus on the benefits that this tool brings to the plant. It is therefore essential to establish a methodology for analysis, based on clear and measurable criteria. Currently, there are different methodologies available in the market to assist with such analysis. These tools can have a quantitative or qualitative focus. The aim of this study is to evaluate three of the best current main performance assessment technologies： Minimum Variance Control-Harris Index; Statistical Process Control （Cp and Cpk）; and the Qin and Yu Index. These indexes were studied for an alumina plant controlled by three MPC （model predictive control） algorithms （GPC （generalized predictive control）, RMPCT （robust multivariable predictive control technology） and ESSMPC （extended state space model predictive controller）） with different results.

A virtual delay queue-based backpressure scheduling for multi-cell cellular edge computing systems

To further improve delay performance in multi-cell cellular edge computing systems,a new delay-driven joint communication and computing resource BP(backpressure)scheduling algorithm is proposed.Firstly,the mathematical models of the communication delay and computing delay in multi-cell cellular edge computing systems are established and expressed as virtual delay queues.Then,based on the virtual delay models,a novel joint wireless subcarrier and virtual machine resource scheduling algorithm is proposed to stabilize the virtual delay queues in the framework of the BP scheduling principle.Finally,the delay performance of the proposed virtual queue-based BP scheduling algorithm is evaluated via simulation experiments and compared with the traditional queue length-based BP scheduling algorithm.Results show that under the considered simulation parameters,the total delay of the proposed BP scheduling algorithm is always lower than that of the traditional queue length-based BP scheduling algorithm.The percentage of the reduced total delay can be as high as 51.29%when the computing resources are heterogeneously configured.Therefore,compared with the traditional queue length-based BP scheduling algorithms,the proposed virtual delay queue-based BP scheduling algorithm can further reduce delay in multi-cell cellular edge computing systems.

Numerical Prediction of Statistical Masonry Wall Fragment Distribution Induced by Blast Loading

The hazard caused by the fragments of damaged structures is usually significant in acci-dental explosions or hostile blast events.A reliable and efficient method to estimate probable fragment size,velocity and launch distance will be useful to assess and design countermeasures to mitigate the possible fragment hazards.This paper presents a numerical method for predicting the size and launch distance of the fragments caused by explosive damage of masonry wall.Numerical simulations with different scaled distances are carried out,and the statistical distribution functions of the fragment size and launch distance in terms of the scaled distance are derived.

Research on Dynamic Parameters of Soil Sites in the Dalian Area

In this paper, dynamic soil parameters derived from Dalian area seismic risk assessment reports are collected. In this study, the measurement data is divided into 7 types, i.e. silty clay, muddy silty clay, clay, medium sand, rock fragments, backfill soil and fully-weathered slate. Statistics of the dynamic parameters of these soils are carried out to obtain the mean values of dynamic shear modulus ratio and damping ratio. Typical drill holes are selected to establish dynamic soil models to investigate the seismic response for various cases. The dynamic parameters of the models are taken from the statistical values of this study, the standard values of code 94 (i.e. the dynamic soil parameters for Dalian seismic microzonation), and the recommended values by Yuan Xiaoming et al. (2000) respectively. The calculated results of peak ground acceleration are compared with the response spectral characteristics. The results show that the statistical values are approximate to the values recommended by Yuan Xiaoming, et al. (2000), but different greatly with the standard values in code 94.

Fastener region location method based on gray-scale mutation

Rail fastener positioning method has high requirements for image quality and positioning accuracy.Therefore,a rail fastener positioning method based on gray mutation is proposed.Firstly,the image is denoised by an improved median filter.Then,according to the characteristics of image frequency domain,the image is decomposed by wavelet transfrom to extract low-frequency component,and the low-frequency component is filtered and processed by gamma transformation to reduce the influence of natural environment factors on image quality.After that,according to the change rule of gray-scale values of different regions in the image,the gray-scale mutation in column and line directions of the image is statistically analyzed,and then the rail surface and the sleeper are located.Finally,the fastener area is accurately located by using the position relationship of the rail surface,the sleeper and the fastener in the image.The experimental results show that the positioning accuracy of the proposed method is 93.19%,which can quickly and effectively locate the fastener region,and has strong environmental adaptability,robustness and practicability.

The Impact of Innovation in Small Industrial Operations to Increased Competitiveness： Empirical Evidence

The present research work in the Small and Medium Enterprise （SME） and industrial sector explains the impact of the relationship among innovation in the SME operations of Aguascalientes to find the most competitive one; to this end, a questionnaire was intended for managers where the results have been analyzed using the statistical package Structural Equation Modeling Programs （EQS） support which through structural equations has responded to the objective. In this sense, it can be concluded that innovation has a positive relationship with the operations and in turn, this relationship shows a positive impact on the competitiveness of SMEs in Aguascalientes. For this study, a sample of 150 companies has been used.

Discussion About Nonlinear Time Series Prediction Using Least Squares Support Vector Machine

The least squares support vector machine (LS-SVM) is used to study the nonlinear time series prediction. First, the parameter gamma and multi-step prediction capabilities of the LS-SVM network are discussed. Then we employ clustering method in the model to prune the number of the support values.. The learning rate and the capabilities of filtering noise for LS-SVM are all greatly improved.

A New Localization Scheme with Statistical Estimation against Wormhole Attack in Wireless Sensor Networks

Wormhole attack is one of the most devastating threats for range-free localization in wireless sensor networks. In this paper, we evaluate three statistical estimation methods with the same network model and geographic information obtailaed by the DV-Hop algorithm. We analyze the limits of Minimum Mean Square Estimate （MMSE）, Least Median of Squares （LMS） and Enhanced greedy At- tack-Resistant MMSE （EARMMSE） and propose an improved EARMMSE with the hop-distance relationship, named EARMMSE＋. Simulation results illustrate the performance of MMSE, LMS and EARMMSE＋ with different anchor fraction, the length of wormhole link and the average local neighborhood and show that EARMMSE＋ outperforms MMSE and LMS.

Statistical evaluation of five failure criteria for intact salt rock

Five multiparameter empirical criteria were exclusively evaluated by comparing them with the strength data covering various stress conditions to find out which failure criterion best fits the test data and describes the mechanical behavior of the salt rock sequence (halite,bedded composite specimens and anhydrite interlayers).Full-scale comparison of all criteria for the three rock types was conducted based on five standard statistics calculated from least squares curve-fitting,which measures both the goodness of fitting and the quality of future prediction.The results indicate that all five nonlinear criteria with a basic power form are efficient in predicting the strength trend in the low tension area as well as in the high compression area of the soft rocks.The parameters obtained for the bedded rock salt are somewhat in the ones for the "pure" rocks and are even closer to those obtained for the halite.The generalized Hoek-Brown criterion is proven to perform best to two rock strength data followed by one for the Bieniawski empirical criterion,thus is the best candidate for the analysis of the salt rock.The Sheorey empirical criterion consistently achieves an intermediate performance for all the three rocks.It seems that the superiority of the poly-axial criteria (the Mogi 1967 criterion and the N-type criterion) over the former three triaxial criteria no longer exists when applied to the conventional triaxial strength data.Besides,the method of tension cut-off was proposed to solve the ambiguity problem of the two poly-axial criteria in the tension field in the plane of the major (σ1) andminor principal stress (σ3).

Prediction of Coastal Fecal Indicator Bacteria Concentrations Using Multivariate Data Analysis

The application of multivariate data analysis, a method for coping with multi-colinearity among independent variables in analyzing coastal water quality data, is presented. This study investigates the statistical regression modeling of FIB （fecal indicator bacteria） concentrations at the outlet of Talbert Marsh in Orange County, California. The multivariate data modeling utilized FIB and physical variables measurements （n = 5,580） collected during a series of longitudinal study of the Talbert Marsh. For the statistical prediction modeling in predicting the FIB concentrations at the outlet of the Talbert Marsh, multivariate analysis techniques such as PCR （principal components regression）, PLS （partial least-squares） regression and SVM （support vector machine） regression were adopted. Statistical modeling results suggest that the statistical modeling predictions are all fell within the reasonable range of actual measurement data. In addition, it is indicated that the accuracy of SVM regression for predicting FIB concentrations at the Talbert Marsh outlet is better than that of other models.

Estimation of Durability of Profit of Small and Medium Enterprises by Statistical Matching

This study computes the durability of Return on Assets （ROA） in small and medium enterprises from different sample datasets. Utilizing information from the Financial Statements Statistics of Corporations by Industry, it verifies the precision of correlation coefficients using the Non-iterative Bayesian-based Imputation （NIBAS） and multiple imputation method for all combinations of common variables with auxiliary files. The following are the three important findings of this paper. First, statistical matching estimates of higher precision can be obtained using key variable sets with higher canonical correlation coefficients. Second, even if the key variable sets have high canonical correlation coefficients, key variables that are correlated extremely strongly with target variables and have high kurtosis should not be used. Finally, using auxiliary flies can improve the precision of statistical matching estimates. Accordingly, the durability of ROA in small and medium enterprises is computed. The author finds that the series of ROA correlation fluctuates for smaller enterprises compared to larger ones, and thus, the vulnerability of ROA in small and medium enterprises can be clarified via statistical matching.

Spatiotemporal Variation of Riverine Nutrients in a Typical Hilly Watershed in Southeast China Using Multivariate Statistics Tools

The water quality of lakes can be degraded by excessive riverine nutrients.Riverine water quality generally varies depending on region and season because of the spatiotemporal variations in natural factors and anthropogenic activities.Monthly water quality measurements of eight water quality variables were analyzed for two years at 16 sites of the Tianmuhu watershed.The variables were examined using hierarchical cluster analysis(HCA) and factor analysis/principal component analysis(FA/PCA) to reveal the spatiotemporal variations in riverine nutrients and to identify their potential sources.HCA revealed three geographical groups and three periods.Two drainages comprising towns and large villages were the most polluted, six drainages comprising widely distributed tea plantations and orchards were moderately polluted, and eight drainages without the factors were the least polluted.The river was most polluted in June when the first heavy rain(daily rainfall > 50 mm) occurs after fertilization and the number of rainy days is most(monthly number of rainy days > 20 days).Moderate pollution was observed from October to May, during which morethan 60% of the total nitrogen fertilizer and all of the phosphorus fertilizer are applied to the cropland, the total manure is applied to tea plantations and orchards, and a monthly rainfall ranging from 0 mm to 164 mm occurs.The remaining months were characterized by frequent raining(i.e., number of rainy days per month ranged from 5 to 24) and little use of fertilizers, and were thus least polluted.FA/PCA identified that the greatest pollution sources were the runoff from tea plantations and orchards,domestic pollution and the surface runoff from towns and villages, and rural sewage, which had extremely high contributions of riverine nitrogen, phosphorus,and chemical oxygen demand, respectively.The tea plantations and orchards promoted by the agricultural comprehensive development(ACD) were not environmentally friendly.Riverine nitrogen is a major water pollution parameter in hilly watersheds affected by ACD, and this parameter would not be reduced unless its loss load through the runoff from tea plantations and orchards is effectively controlled.

Selective transmission and channel estimation in massive MIMO systems

Massive MIMO systems have got extraordinary spectral efficiency using a large number of base station antennas,but it is in the challenge of pilot contamination using the aligned pilots.To address this issue,a selective transmission is proposed using time-shifted pilots with cell grouping,where the strong interfering users in downlink transmission cells are temporally stopped during the pilots transmission in uplink cells.Based on the spatial characteristics of physical channel models,the strong interfering users are selected to minimize the inter-cell interference and the cell grouping is designed to have less temporally stopped users within a smaller area.Furthermore,a Kalman estimator is proposed to reduce the unexpected effect of residual interferences in channel estimation,which exploits both the spatial-time correlation of channels and the share of the interference information.The numerical results show that our scheme significantly improves the channel estimation accuracy and the data rates.

Development of Small and Medium Enterprises （SMEs） Accounting Information System in Cluster of Kampung Laweyan Batik, Surakarta, Indonesia

The role of small and medium enterprises （SMEs） in the economy of a country was quite strategic, however the tightness of the competition, has allowed the SMEs into disadvantageous position. The SMEs need a precise accounting information system, thus the SMEs could improve the accuracy, validation data, productivity, and the competitiveness of enterprises. The problem of this research is how the SMEs accounting information systems in a cluster of Kampung Batik Laweyan Surakarta. To develop accounting information systems in a SMEs cluster of Kampung Batik Laweyan Surakarta, this research used research and development （R＆D） method. Data obtained through analysis of the company＇s business processes. Results of data analysis used to develop accounting information systems in a SMEs cluster of Kampung Batik Laweyan Surakarta. Accounting information system development consists of the structure of SMEs organizations, the general design of accounting information systems of the SMEs, flowchart and documentation of the SMEs accounting information systems, and accounting software of the SMEs