新型可调间隙RV减速器回差分析与实验研究

推导了变厚齿轮调隙量与回差之间的关系式及计算内啮合变厚齿轮副和变厚齿轮RV减速器的回差计算公式 。

基于蒙特卡罗模拟的精密减速器公差分组匹配回差分析

回差是影响精密减速器传动系统精度的重要因素,而影响减速器回差的公差较多,这些公差若不加区别任意组合将有超出回差要求范围的风险。目前,公差分析所使用的传统概率法仅满足于公差带为正态分布的计算,且这些公差分析大多针对特定类型的传动系统。因此,基于等概率抽样,将蒙特卡罗模拟应用到传动系统公差分组匹配优化中,可以克服公差带分布类型和传动系统类型的限制;并结合算例说明其达到了提高精密减速器回差精度和降低成本的目的。

基于椭圆法的摆线轮齿廓修形

为得到更加理想的摆线轮齿廓线型,提出一种新的摆线轮齿廓修形方法。在保证短幅系数,偏心距不变的情况下,利用椭圆对摆线轮的标准理论轮廓线滚动切割修形,得到修形后的齿面轮廓线,并推导出其方程表达式。与常用的齿廓修形方法相比,修形后的齿廓曲线在主要工作段更加逼近完全共轭齿廓,并且通过控制椭圆的形状参数,可对摆线轮与针齿轮的啮合间隙进行调整,简单灵活。分析该修形齿廓的法向齿廓间隙、初始啮合间隙、接触应力以及回差影响,验证了该修形方法的合理性。

基于PFC^(3D)对无底柱分段崩落法结构参数优化研究

为了减少矿山企业的采矿成本,提高矿山的经济效益,对无底柱分段崩落法的结构参数、多分段放矿等方面进行研究,分析与矿石的回收率和贫化率的关系。探讨以大间距结构参数为理论基础,结合矿山的实际放矿参数,确定正交试验因素,采用室内多分段放矿模型,分别对低贫化放矿和矿山现行截止品位放矿进行了试验,分别分析放矿结构参数与矿石回收率和贫化率的关系。采用计算机PFC^(3D)软件模拟低贫化放矿,将模拟所得数据采用回贫差因素分析方法进行分析,利用ORIGIN软件采用响应面法拟合函数分析回贫差和结构参数的关系,最后分析矿石回贫差与无底柱分段崩落法各结构参数的关系,结果表明提出的该矿山的无底柱分段崩落法结构参数为最优值。

Comprehensive modeling approach of axial ultrasonic vibration grinding force

The theoretical model of axial ultrasonic vibration grinding force is built on the basis of a mathematical model of cutting deforming force deduced from the assumptions of thickness of the undeformed debris under Rayleigh distribution and a mathematical model of friction based on the theoretical analysis of relative sliding velocity of abrasive and workpiece. Then, the coefficients of the ultrasonic vibration grinding force model are calculated through analysis of nonlinear regression of the theoretical model by using MATLAB, and the law of influence of grinding depth, workpiece speed, frequency and amplitude of the mill on the grinding force is summarized after applying the model to analyze the ultrasonic grinding force. The result of the above-mentioned law shows that the grinding force decreases as frequency and amplitude increase, while increases as grinding depth and workpiece speed increase; the maximum relative error of prediction and experimental values of the normal grinding force is 11.47% and its average relative error is 5.41%; the maximum relative error of the tangential grinding force is 10.14% and its average relative error is 4.29%. The result of employing regression equation to predict ultrasonic grinding force approximates to the experimental data, therefore the accuracy and reliability of the model is verified.

Shear creep characteristics and constitutive model of limestone

The characters of limestone in weak interlayer of a high rocky slope in Xuzhou, China, are studied by shear static test and shear creep test. The results show that limestone specimens have attenuation creep properties and constant rate creep properties, almost have no accelerated creep properties. The exponential type empirical formula is selected to fit creep grading curves by polynomial regression analysis method, and the square sums of the fitting results residual are in the order of 10^(-7). Then grade creep curves at every shear loads are set up. Combining creep rate-time curve, the creep properties of limestone are analyzed. As the physical meaning of component model is clearer, the Poytin–Thomson model is set up. Through the least square method, the optimal parameters of Poytin–Thomson model are obtained,and the sums of squared residuals belong to 10^(-3)order of magnitude, which can meet the accuracy requirements of engineering calculation. So the Poytin–Thomson model can reflect the shear creep characteristics of limestone very well.

Accuracy Analysis on Bundle Adjustment of Remote Sensing Images Based on Dual Quaternion

A bundle adjustment method of remote sensing images based on dual quaternion is presented,which conducted the uniform disposal corresponding location and attitude of sequence images by the dual quaternion.The constraint relationship of image itself and sequence images is constructed to compensate the systematic errors.The feasibility of this method used in bundle adjustment is theoretically tested by the analysis of the structural characteristics of error equation and normal equation based on dual quaternion.Different distributions of control points and stepwise regression analysis are introduced into the experiment for RC30 image.The results show that the adjustment accuracy can achieve 0.2min plane and 1min elevation.As a result,this method provides a new technique for geometric location problem of remote sensing images.

Regression analysis of major parameters affecting the intensity of coal and gas outbursts in laboratory

Estimating the intensity of outbursts of coal and gas is important as the intensity and frequency of outbursts of coal and gas tend to increase in deep mining. Fully understanding the major factors contributing to coal and gas outbursts is significant in the evaluation of the intensity of the outburst. In this paper, we discuss the correlation between these major factors and the intensity of the outburst using Analysis of Variance(ANOVA) and Contingency Table Analysis(CTA). Regression analysis is used to evaluate the impact of these major factors on the intensity of outbursts based on physical experiments. Based on the evaluation, two simple models in terms of multiple linear and nonlinear regression were constructed for the prediction of the intensity of the outburst. The results show that the gas pressure and initial moisture in the coal mass could be the most significant factors compared to the weakest factor-porosity. The P values from Fisher's exact test in CTA are: moisture(0.019), geostress(0.290), porosity(0.650), and gas pressure(0.031). P values from ANOVA are moisture(0.094), geostress(0.077), porosity(0.420), and gas pressure(0.051). Furthermore, the multiple nonlinear regression model(RMSE: 3.870) is more accurate than the linear regression model(RMSE: 4.091).

Analysis of passenger boarding time difference between adults and seniors based on smart card data

As an essential component of bus dwelling time, passenger boarding time has a significant impact on bus running reliability and service quality. In order to understand the passengers’ boarding process and mitigate passenger boarding time, a regression analysis framework is proposed to capture the difference and influential factors of boarding time for adult and elderly passengers based on smart card data from Changzhou. Boarding gap, the time difference between two consecutive smart card tapping records, is calculated to approximate passenger boarding time. Analysis of variance is applied to identify whether the difference in boarding time between adults and seniors is statistically significant. The multivariate regression modeling approach is implemented to analyze the influences of passenger types, marginal effects of each additional boarding passenger and bus floor types on the total boarding time at each stop. Results show that a constant difference exists in boarding time between adults and seniors even without considering the specific bus characteristics. The average passenger boarding time decreases when the number of passenger increases. The existence of two entrance steps delays the boarding process, especially for elderly passengers.

An Empirical Analysis of Employment Stability and the Wage Gap of Rural Migrants in China Based on Quantile Regression

Under the background of accelerated integrated urban-rural development, this paper offers an analysis on the short-term employment of rural migrants in China and resulting wage gap between long-term and short-term rural migrants. On the basis of correcting for sample selection problems arising from labor market participation and short-term employment, rural migrants＇ wage function is estimated using quantile regression method, and wage gap between long-term and short-term rural migrants is decomposed using MM method. Our empirical results suggest that those with a higher level of education, training experience and local employment recommended by family relations or in formal labor market are more likely to secure long-term labor contract,＂ region and education have significant contributions to the wage of rural migrants,＂ rural migrants of both long- and short-term contract types have great gaps at the bottom of salary distribution; and there exists a sticky floor effect in wage difference of rural migrants. These results have important policy implications in enhancing employment stability of rural migrants, improving income distribution equity, speeding up the process of urbanization, and balancing regional development.

Do Satisfaction and Loyalty Have a Linear Relationship？ Effect of the Education Level on Arts Participation

This paper aims to explore the relationship between perceived satisfaction and loyalty of Spanish arts participants. Evidence suggests that customer satisfaction plays a key role in an organization＇s ability to maintain a relationship with its customers. We examined the link between satisfaction and loyalty within a theoretical framework based on an empirical study in which data from more than 14,000 respondents were obtained. This data allowed us to evaluate the arts consumer from an attitudinal and behavioral perspective looking at their interests, satisfaction level, frequency of attendance, and compare it using the participant＇s education level. A descriptive statistical analysis using ANOVA （analysis of variance）, correlation, partial correlation, and multiple regression provided evidence that, in the context of experiencing an arts show, satisfaction does not have any impact on loyalty but education level plays a significant role in people＇s interest and loyalty.

Analysis of gender＇s role on voluntary tendency of potential/active volunteers via logistic regression modeling： The case of Canakkale Onsekiz Mart University

From economy to political administrations, education to health, environment to human rights, many problems we met have gained a global importance in recent days. Existing state systems, political parties and nation states are not adequate for solving these problems in question effectively on their own. Not only governments and local authorities but also voluntary organizations based on completely voluntary activities have significant roles in solving these problems. Effective performance of voluntary organizations depends on increasing volunteer population. Individuals＇ attitudes or their perception of understanding volunteerism play an important role in their contributions to voluntary organizations. The aim of this study is to determine individuals＇ ways of perceiving volunteerism concept and their tendency towards it. Furthermore, differences between men and women＇s perception and attitudes towards volunteerism concept have been examined. For this purpose, a survey has been conducted over university students of bachelor＇s degree. Tendencies and attitudes towards volunteerism compared to gender differences have been tested via logistic regression method. Research results reveal that women take part in voluntary activities more than men and women perceive volunteerism as ＂a political position＂ while men perceive volunteerism as ＂a learning atmosphere and learning process＂.

Research into the Assessment of the Intercultural Sensitivity Among University Students of Science and Technology

Globalization makes people from diverse cultural backgrounds communicate effectively. To be a global citizen has become the goal of our education. Landis and Bhagat （1996） argued that intercultural sensitivity is crucial to enable people to live and work with others from different cultural backgrounds. With higher intercultural sensitivity, one will be more global as his understanding of cultural difference becomes more sophisticated. In this present study, the intercultural sensitivity of different majors from a private institute of technology in the north of Taiwan was investigated, using the ISS （Intercultural Sensitivity Scale） developed by Chen and Starosta （2000）. Based on a survey of 358 participants from Nursing Department and Department of Nutrition and Health Sciences, this study focused on five dimensions of the intercultural sensitivity and the participants＇ demographic factors affecting their performance on intercultural sensitivity. The five dimensions included in this study were： （1） interaction engagement, （2） interaction confidence, （3） respect for cultural differences, （4） interaction enjoyment, and （5） interaction attentiveness. Among the five dimensions of intercultural sensitivity, the participants had the highest score on the dimension of ＂respect for the cultural differences＂ and had the lowest score on the dimension of ＂interaction confidence＂. Results generated by stepwise multiple regression indicated ＂decision of studying abroad＂ and ＂experiences of living abroad＂ could effectively predict the participants＇ intercultural sensitivity.

Sharp learning rates of coefficient-based l^q-regularized regression with indefinite kernels

Learning with coefficient-based regularization has attracted a considerable amount of attention in recent years, on both theoretical analysis and applications. In this paper, we study coefficient-based learning scheme （CBLS） for regression problem with /q-regularizer （1 〈 q ≤ 2）. Our analysis is conducted under more general conditions, and particularly the kernel function is not necessarily positive definite. This paper applies concentration inequality with/2-empirical covering numbers to present an elaborate capacity dependence analysis for CBLS, which yields sharper estimates than existing bounds. Moreover, we estimate the regularization error to support our assumptions in error analysis, also provide an illustrative example to further verify the theoretical results.

Heteroscedasticity Detection and Estimation with Quantile Difference Method

When dealing with regression analysis,heteroscedasticity is a problem that the authors have to face with.Especially if little information can be got in advance,detection of heteroscedasticity as well as estimation of statistical models could be even more difficult.To this end,this paper proposes a quantile difference method(QDM) that can effectively estimate the heteroscedastic function.This method,being completely free from the estimation of mean regression function,is simple,robust and easy to implement.Moreover,the QDM method enables the detection of heteroscedasticity without any restrictions on error terms,consequently being widely applied.What is worth mentioning is that based on the proposed approach estimators of both mean regression function and heteroscedastic function can be obtained.In the end,the authors conduct some simulations to examine the performance of the proposed methods and use a real data to make an illustration.

VARIABLE SELECTION FOR RECURRENT EVENT DATA WITH INFORMATIVE CENSORING

Recurrent events data with a terminal event （e.g., death） often arise in clinical and ob- servational studies. Variable selection is an important issue in all regression analysis. In this paper, the authors first propose the estimation methods to select the significant variables, and then prove the asymptotic behavior of the proposed estimator. Furthermore, the authors discuss the computing algorithm to assess the proposed estimator via the linear function approximation and generalized cross validation method for determination of the tuning parameters. Finally, the finite sample estimation for the asymptotical covariance matrix is also proposed.