深度域地震子波提取方法综述

由于深度域地震子波具有对介质速度依赖的特性,褶积模型无法直接用于提取深度域地震子波。准确提取深度域地震子波对于深度域地震资料的反演和解释具有重要意义。首先,分析了深度域地震子波提取中存在的2个主要问题,即深度域地震子波对介质速度的依赖特性和深度域测井数据与地震数据的采样间隔非一致性,并提出了相应对策。然后,对目前已有的深度域地震子波提取方法进行了梳理,根据是否在方法中用到测井信息,将方法分为确定性地震子波提取方法和统计性地震子波提取方法2大类,并对每一种方法的优缺点及适用条件进行了总结。最后,对深度域地震子波提取方法的未来发展提出以下建议:①深度域统计性地震子波提取方法有待进一步发展;②将地震反演结果与测井资料之间的相关性纳入到子波提取结果优劣的评价标准中;③使用地震子波模型减少子波提取中需要求解的未知量个数,以提升方法的计算效率;④将一维深度域地震子波提取方法扩展至提取二维和三维深度域地震子波;⑤利用机器学习方法的优势,建立不依赖褶积模型的深度域地震子波提取方法,或建立可以省去子波提取的深度域地震反演方法。

Improvement for design of beam structures in large vibrating screen considering bending and random vibration

Demand for large vibrating screen is huge in the mineral processing industry. As bending and random vibration are not considered in a traditional design method for beam structures of a large vibrating screen, fatigue damage occurs frequently to affect the screening performance. This work aims to conduct a systematic mechanics analysis of the beam structures and improve the design method. Total motion of a beam structure in screening process can be decomposed into the traditional followed rigid translation(FRT), bending vibration(BV) and axial linear-distributed random rigid translation(ALRRT) excited by the side-plates. When treated as a generalized single-degree-of-freedom(SDOF) elastic system analytically, the BV can be solved by the Rayleigh's method. Stochastic analysis for random process is conducted for the detailed ALRRT calculation. Expressions for the mechanics property, namely, the shearing force and bending-moment with respect to BV and ALRRT, are derived, respectively. Experimental and numerical investigations demonstrate that the largest BV exists at the beam center and can be nearly ignored in comparison with the FRT during a simplified engineering design. With the BV and FRT considered, the mechanics property accords well with the practical situation with the maximum error of 6.33%, which is less than that obtained by traditional method.

AN EFFECTIVE IMAGE RETRIEVAL METHOD BASED ON KERNEL DENSITY ESTIMATION OF COLLAGE ERROR AND MOMENT INVARIANTS

In this paper, we propose a new method that combines collage error in fractal domain and Hu moment invariants for image retrieval with a statistical method - variable bandwidth Kernel Density Estimation (KDE). The proposed method is called CHK (KDE of Collage error and Hu moment) and it is tested on the Vistex texture database with 640 natural images. Experimental results show that the Average Retrieval Rate (ARR) can reach into 78.18%, which demonstrates that the proposed method performs better than the one with parameters respectively as well as the commonly used histogram method both on retrieval rate and retrieval time.

A Comprehensive Method for Evaluating Precision of Transfer Alignment on a Moving Base

In this study, we propose the use of the Degree of Alignment(DOA) in engineering applications for evaluating the precision of and identifying the transfer alignment on a moving base. First, we derive the statistical formula on the basis of estimations. Next, we design a scheme for evaluating the transfer alignment on a moving base, for which the attitude error cannot be directly measured. Then, we build a mathematic estimation model and discuss Fixed Point Smoothing(FPS), Returns to Scale(RTS), Inverted Sequence Recursive Estimation(ISRE), and Kalman filter estimation methods, which can be used when evaluating alignment accuracy. Our theoretical calculations and simulated analyses show that the DOA reflects not only the alignment time and accuracy but also differences in the maneuver schemes, and is suitable for use as an integrated evaluation index. Furthermore, all four of these algorithms can be used to identify the transfer alignment and evaluate its accuracy. We recommend RTS in particular for engineering applications. Generalized DOAs should be calculated according to the tactical requirements.

Regression-Based Artificial Neural Network Methodology in Response Surface Methodology

Response surface methodology (RSM) is an important tool for process parameter optimization, robust design and other quality improvement efforts. When the relationship between influential input variables and output response is very complex, it’s hard to find the real response surface using RSM. In recent years artificial neural network(ANN) has been used in RSM. But the classical ANN does not work well under the constraints of real applications. An algorithm of regression-based ANN(R-ANN) is proposed in this paper, which is a supplement to the classical ANN methodology. It makes network closer to the response surface, so that training time is reduced and robustness is strengthened. The procedure of improving ANN by regressions is described and the comparisons among R-ANN,RSM and classical ANN are computed graphically in three examples. Our research shows that the R-ANN methodology is a good supplement to the RSM and classical ANN methodology, which can yield lower standard error of prediction under conditions that the scope of experiment is rigidly restricted.

International Accounting Standards Board （IASB） and Financial Accounting Standards Board （FASB） Convergence Project： Where Are They Now？

The convergence project between the International Accounting Standards Board （IASB） and the Financial Accounting Standards Board （FASB） in the United States （US） was signed on September 18, 2002 in Norwalk, Connecticut in the US. The first is responsible for issuing International Financial Reporting Standards （IFRS） nowadays, which were created 40 years ago. More than one century ago, local regulations are used in the US. The boards differ in years of experience. With the signing of the agreement, both institutions are working to reduce the divergence of accounting. Although they have made a significant progress, it is appropriate to examine whether the difference in approaches to accounting will affect the achieved agreements. It is relevant to investigate whether the years leading the standards adopted in different countries will impact the final result. The date of completion of the project has been postponed and still has not indicated the date of termination. This research is an analysis of the importance of the convergence of accounting standards at a global level. The study presents statistics on the status of the adoption of international standards by country. The study shows a summary of the expressions made by the directors of both boards about the future of the project.

Spatial Variability of Soil Organic Carbon in Different Hillslope Positions in Toshan Area, Golestan Province, Iran: Geostatistical Approaches

Accessibility to organic carbon(OC) budget is required for sustainable agricultural development and ecosystem preservation and restoration. Using geostatistical models to describe and demonstrate the spatial variability of soil organic carbon(SOC) will lead to a greater understanding of this dynamics. The aim of this paper is to present the relationships between the spatial variability of SOC and the topographic features by using geostatistical methods on a loess mountain-slope in Toshan region, Golestan Province, northern Iran. Hence, 234 soil samples were collected in a regular grid that covered different parts of the slope. The results showed that such factors as silt, clay, saturated moisture content, mean weighted diameter(MWD) and bulk density were all correlated to the OC content in different slope positions, and the spatial variability of SOC more to slope positions and elevations. The coefficient of variation(CV) indicated that the variability of SOC was moderate in different slope positions and for the mountain-slope as a whole. However, the higher variability of SOC(CV = 45.6%) was shown in the back-slope positions. Also, the ordinary cokriging method for clay as covariant gave better results in evaluating SOC for the whole slope with the RMSE value 0.2552 in comparison with the kriging and the inverse distance weighted(IDW) methods. The interpolation map of OC for the slope under investigation showed lowering SOC concentrations versus increasing elevation and slope gradient. The spatial correlation ratio was different between various slope positions and related to the topographic texture.

Fault detection of large-scale process control system with higher-order statistical and interpretative structural model

Nonlinear characteristic fault detection and diagnosis method based on higher-order statistical(HOS) is an effective data-driven method, but the calculation costs much for a large-scale process control system. An HOS-ISM fault diagnosis framework combining interpretative structural model(ISM) and HOS is proposed:(1) the adjacency matrix is determined by partial correlation coefficient;(2) the modified adjacency matrix is defined by directed graph with prior knowledge of process piping and instrument diagram;(3) interpretative structural for large-scale process control system is built by this ISM method; and(4) non-Gaussianity index, nonlinearity index, and total nonlinearity index are calculated dynamically based on interpretative structural to effectively eliminate uncertainty of the nonlinear characteristic diagnostic method with reasonable sampling period and data window. The proposed HOS-ISM fault diagnosis framework is verified by the Tennessee Eastman process and presents improvement for highly non-linear characteristic for selected fault cases.

Analysis of Properties of Thrust Bearing in Ship Propulsion System

Thrust bearing is a key component of the propulsion system of a ship. It transfers the propulsive forces from the propeller to the ship＇s hull, allowing the propeller to push the ship ahead. The performance of a thrust bearing pad is critical. When the thrust bearing becomes damaged, it can cause the ship to lose power and can also affect its operational safety. For this paper, the distribution of the pressure field of a thrust pad was calculated with numerical method, applying Reynolds equation. Thrust bearing properties for loads were analyzed, given variations in outlet thickness of the pad and variations between the load and the slope of the pad. It was noticed that the distribution of pressure was uneven. As a result, increases of both the outlet thickness and the slope coefficient of the pad were able to improve load beating capability.

Two-and Three-Dimensional Urban Core Determinants of the Urban Heat Island： A Statistical Approach

There is no doubt that the UHI （urban heat island） is a mounting problem in built-up environments, due to the energy retention by surface dense building materials, leading to increased temperatures, air pollution, and energy consumption. Much of the earlier research on the UHI has used two-dimensional （2-D） information, such as land uses and the distribution of vegetation. In the case of homogeneous land uses, it is possible to predict surface temperatures with reasonable accuracy with 2-D information. However, three-dimensional （3-D） information is necessary to analyze more complex sites, including dense building clusters. In this research, 3-D building geometry information is combined with 2-D urban surface information to examine the relationship between urban characteristics and temperature. The research includes the following stages： （1） estimating urban temperature; （2） developing a 3-D city model; （3） generating geometric parameters; and （4） conducting statistical analyses using both linear and non-linear regression models. The implications of the results are discussed, providing guidelines for policies aiming to reduce the UHI.

A Homogeneous Linear Estimation Method for System Error in Data Assimilation

In this paper, a new bias estimation method is proposed and applied in a regional ensemble Kalman filter （EnKF） based on the Weather Research and Forecasting （WRF） Model. The method is based on a homogeneous linear bias model, and the model bias is estimated using statistics at each assimilation cycle, which is different from the state augmentation methods proposed in pre- vious literatures. The new method provides a good estimation for the model bias of some specific variables, such as sea level pres- sure （SLP）. A series of numerical experiments with EnKF are performed to examine the new method under a severe weather condi- tion. Results show the positive effect of the method on the forecasting of circulation pattern and meso-scale systems, and the reduc- tion of analysis errors. The background error covarianee structures of surface variables and the effects of model system bias on EnKF are also studied under the error covariance structures and a new concept ＇correlation scale＇ is introduced. However, the new method needs further evaluation with more cases of assimilation.

Statistical analysis of fracture properties based on particle swarm optimization and Pearson correlation coefficient method

Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.

Type Selection of Burning Equipment for Slagging-Coal Boilers

The type selection of burning equipment for boilers is affected significantly by the slagging characteristics of coal. Based on the engineering statistics method, the designed furnace parameters are obtained from the 600-MW and 1 000-MW boilers with tangential firing and wall firing. The power and arrangement of the burners are analyzed. Their impacts on slagging on heating surfaces and the carbon contents in the ash and cinders are also discussed. Thermal parameters of furnace are recommended for boilers of 600 MW and 1 000 MW firing slagging coal in the design. The static or rotary classifier should be the first choice for the pulverizing system.

Economic Consequences of Gender Equality in Europe

This paper shows influence of gender equality on economy where it analyzed how gender equality in Europe has affected on the development of the frozen food industry and services related to childcare. The development of these industries has given a positive impulse to the development of the whole economy. In this analysis, it is used multiple regressions as one of the most important statistical methods. In the first part of this paper, it shows the connection among the growth of female employment, growth in frozen food expenditure and growth of GDP in United Kingdom. In the second part of paper, it shows the relationship among the growth of labor force participation of women, growth of number of kindergarten and growth of GDP in Hungary. To proof these relationships, it used a multiple regression model. This statistical model was tested by using the T schedule which showed that the model in both the analyses is correct. At the end of the paper, it presents that employment rate and GDP behaves in the same way in European Union. These analyses show that it is necessary to continue to strengthen gender equality if the policy makers want to achieve even greater economic growth. The issue of gender equality is a very important factor in creating employment policy, and statisticians should be more involved in process of employment policy and gender equality

A TREND DISPLACEMENT ANALYSIS FOR SPACE AND TIME ON XINTAN LANDSLIDE

This paper, having made systematic trend analysis on the front and rear segments of Xintan landslide for space and time respectively by using matbematical statistical principles,discovered that there is obvious trend displacement Of the monitoring points in the rear margin area of the slope and the rates of trend displacement gradually increase with time whereas there is no trend displacement of the monitoring points in the front margin area. This result suggests that the rear margin area of segment is an area of overall sliding and is transforming towards destabilization whereas the front margin area is an area of relative stability. This analytical result well coincides with the conclusion of evaluation on dynamic stability. The analytical result mentioned above shows that the medium to short term forecast and prediction of slope stability can be made by using trend displacement analysis technique in order to achieve the goal of timely evaluation and prevention.

Parameter design and performance analysis of zero inertia continuously variable transmission system

In order to solve the problem of weak power performance of vehicle equipped with continuously variable transmission(CVT) system working under transient operating conditions, a new CVT equipped with planetary gear mechanism and flywheel was researched, a design method of transmission parameter optimization was proposed, and the comprehensive matching control strategy was established for the new transmission system. Fuzzy controllers for throttle opening and CVT speed ratio were designed, and power performance and fuel economy of both vehicles respectively equipped with conventional CVT system and new transmission system wrere compared and analyzed by simulation. The results show that power performance and fuel economy of the vehicle equipped with new transmission system are better than that equipped with conventional CVT, thus the rationality of the parameter design method and control algorithm are verified.

Adaptive and local analysis of climate data

This paper focuses on how to extract physically meaningful information from climate data,with emphases placed on adaptive and local analysis. It is argued that many traditional statistical analysis methods with rigorous mathematical footing may not be efficient in extracting essential physical information from climate data;rather,adaptive and local analysis methods that agree well with fundamental physical principles are more capable of capturing key information of climate data. To illustrate the improved power of adaptive and local analysis of climate data,we also introduce briefly the empirical mode decomposition and its later developments.

The Selection and Application of Non-Conventional Decoration Materials in Indoor Design

In indoor design innovation, the material role can not be ignored. In indoor design, using non-conventional decoration materials can make space more personalized and charming. This is one of the material innovation modes and also one of the indoor design innovation modes. The design method should obtain more attention.

Design of Weigh Feeder Control System for Energy Saving Using Performance-Adaptive Method

This paper discusses a design method for the control system of a weigh feeder that supplies powder and granular material at a constant rate. Most weigh feeders employed in industry are controlled by proportional and integral （PI） compensation, and the control performance is decided by the selection of parameters. To attain advanced control performance by PI control, the PI parameters are designed on the basis of generalized minimum variance control （GMVC）. In this study, to achieve user-specified control performance by GMVC-based PI control, the design parameters of GMVC are automatically adjusted using a performance-adaptive method. The control performance discussed in this study consists of the variance of the control error and that of the difference in the control input. In a conventional performance-adaptive method, the variance of the control error is reduced. In this study, to reduce energy consumption and to achieve user-specified control performance, the variance of the difference in the control input is specified and the design parameter is determined. To demonstrate its effectiveness, the proposed method is applied to an actual weigh feeder.

Design and Application of XL-1 Psychological Quality Assessment Device

Objective: Through the application of the physiological indicator of heart rate variability by some equipments, to assess the psychological quality objectively, quickly and accurately instead of subjectively in the current methods of the assessment. Methods: Apply the new psychological assessment system to collect the signal of heart rate variability which will be converted to waveforms in time-domain and frequency-domain to analyze people's psychological state. Results: According to heart rate variability parameters in the time domain and frequency domain, we can analyze the autonomic nervous system functions objectively and accurately, then assess mental state. Conclusion: Heart rate variability plays an important role in the psychological assessment system, which has broad prospects for the future development.