An artificial neural network approach to prediction of the colorimetric values of the stripped cotton fabrics

This paper presents an artificial neural network (ANN) modeling by Levenberg-Marquardt (LM) algorithm for predicting the colorimetric values of the stripped cotton fabrics dyed using commercial reactive dyes. Achieving the expected efficiency in the application of stripping process is a very important aspect for the success of the reproduction. In the study, the predictions of L* and ΔE colorimetric values of stripped cotton samples for different stripping applications by artificial neural network are reported. We set up different network structures with different number of nodes in the hidden layer, the number of inputs and MSE of results as stopping criteria in order to get the best fitting model. According to the result of the best neural network models predicting L* and ΔE, we achieved 97 % of R for both of them. We are able to predict the L* value of the stripped samples using some working parameters as inputs with only 1.2 % error. We think that our results are very promising and the predictions of L* and ΔE values of stripped samples before applying any process are possible using the ANN model set up in the study, especially for L*.     

Effects of the Sire and District of A1 on Cow Fertility

Insemination results per bull and district of AI (or technician) were analysed in a 5 year study. Return Rates (RR) were registered between Oct. 1976 and Sept. 1981. Data included 856 850 first AI made by 56 technicians. Depending on years, AI were made with the semen of 81 to 103 bulls of 5 breeds. Only bulls which performed at least 500 AI's per year were taken into account. A first analysis made with the data of 14 bulls represented during the 5 years show that: 1) the breed, the bull within breed and district of AI (or technician) were the most important factors influencing RR. RR were less affected by other factors such as the size of the herd or the year. 2) results given for successive RR were nearly identical from RR₂₄ to RR₉₀. 3) the effect of breed, bull and district of AI were less important on the variable illustrating more specificially late return in oestrus (RR_25–300). Yearly analysis involving larger number of bulls gave very similar results to the 5 year study. Variability due to the district of AI (or technician) and to the bull were of the same magnitude. Maximum differences between bulls or districts varied from 10% (RR₂₄) to 20% (RR₉₀). As strong relationships between bull and district of AI or technician were found, complementary analyses from the 1978 set of data were made to investigate how the variability due to the district of AI could introduce bias when estimating bull's RR. Comparisons between models were made on the basis of correlations between a reference model including a district effect and reduced models. For RR₂₄ and RR₉₀ correlations between solutions were always higher than 0.97. This show that if sufficient number of AI's per bull are performed no major bias is introduced and the district of AI or technician is neglectable when evaluating bull's RR .     

基于响应曲面法的女性假人颈部减速特性建模

混Ⅲ5百分位女性假人颈部标定试验中,减速特性遇到问题较多,试验发现标定温度、蜂窝铝孔数及裁剪方式及碰撞速度均会影响颈部标定结果。本文利用中心复合设计,采用响应曲面法建立颈部减速特性模型,同时结合方差分析(ANOVA),详尽分析上述因素对标定结果的影响趋势。进而优化影响参数的选取,从而极大地提高标定效率。     

固定裸沙地粗糙度动力学特性的分析与研究

主要利用曲线拟合的方法,结合野外实测数据计算固定裸沙地的粗糙度,对计算出的粗糙度和风速进行回归分析和方差分析,由此对粗糙度的动力学特性进行分析与研究,结果表明:在下垫面不发生改变的情况下,空气动力学粗糙度与风速的增长呈负相关关系,即粗糙度具有动力学特性。但是由于两者相关程度并不显著,因此在实际工作中可以忽略风速对粗糙度的影响。     

集体农地管理权配置对农地承包权稳定性的影响

论文在从理论上分析集体农地管理权与农地承包经营权稳定性之间相关关系的基础上，通过运用方差分析方法对生态脆弱区江西省兴国县、上饶县、余江县样本村农户调查数据的分析，结果表明：从土地调整的不同组织者类型的平均土地调整次数来看，在调查区，尽管基层政权组织及其延伸组织会介入农村土地或组织农村土地承包经营权调整事务，但土地调整的愿望最强烈的还是农民自己，而行政组织及准行政组织(行政村与村小组)土地调整的需求不如农民自己强烈。最后，论文从改善集体农地管理权、提高农地承包权稳定性方面，提出了开展水土保持的政策建议。     

多变异来源的工序方法在机械制造过程中的应用

统计过程控制所用的传统的休哈特控制图只能控制单一变异来源。本文讨论了质量特征值来自多个变异来源的工序控制情况,通过多变异分析,提出了一种针对每个变异来源采用单值控制图分别进行控制的工序控制方法,并以轴加工为例介绍了这种方法的应用。     

Identifying physiological traits associated with improved drought resistance in winter wheat

The association of specific target traits for drought resistance (early flowering, high accumulation of stem water soluble carbohydrate (WSC) reserves, presence of awns and high green flag-leaf area persistence) with yield performance under late-season drought was analyzed utilizing two doubled-haploid (DH) populations derived from crosses between Beaver × Soissons and Rialto × Spark in two seasons 2000/2001 and 2001/2002. The aim was to quantify associations between target traits and yield responses to drought, and to prioritize traits for drought resistance. Flowering time variation had a neutral effect on the absolute yield loss under drought, suggesting there may be a trade-off between water-saving behaviour in the shorter pre-flowering period with early flowering and a reduced capacity to access water associated with a smaller rooting system. The presence of awns also had a neutral effect on yield loss under drought amongst lines of the Beaver × Soissons population. The potential advantages of awns for increasing water-use efficiency and sensible heat transfer responsible for a cooler canopy appeared to be of less significance under moderate droughts in the UK than under severe droughts in other regions worldwide. The value of large stem soluble carbohydrate reserves for drought environments alone could not be confirmed in the UK environment. Stem WSC was positively associated with grain yield under both irrigation and drought. The genetic trait which showed the clearest correlation with the ability to maintain yield under drought was green flag-leaf area persistence. Averaged across years, the positive phenotypic correlation of this trait with yield under drought amongst DH lines of the Beaver × Soissons population (r = 0.49; p ≤ 0.001) indicated the potential use of this trait as a selection criterion for yield under drought. It is suggested that screens for this trait including marker-assisted selection would have value in future breeding programmes aimed at improving yields in high yielding, rainfed environments, but where drought can also be a problem, such as the UK.     

What's normal anyway? Residual plots are more telling than significance tests when checking ANOVA assumptions

We consider two questions important for applying analysis of variance (ANOVA): Should normality be checked on the raw data or on the residuals (or is it immaterial which of the two approaches we take)? Should normality and homogeneity of variance be checked using significance tests or diagnostic plots (or both)? Based on two examples, we show that residuals should be used for model checking and that residual plots are better for checking ANOVA assumptions than statistical tests. We also discuss why one should be very cautious when using statistical tests to check the assumptions.     

抗生素及其替代品饲喂的肉鸡(狗)中铬含量对比研究

选用18只分3组处理(分别在鸡、狗日粮中添加蜂胶、芦荟粉和金霉素)的45日龄肉鸡、60日龄狗，停药(金霉素)12小时取样，对比研究抗生素及其替代品对其铬含量的影响。用石墨炉原子吸收法测定出用蜂胶、芦荟粉和金霉素饲喂的鸡(狗)肉中铬含量均低于我国无公害畜禽肉安全要求(GB18406．3—2001)中规定的铬的最高限量，且3组肉鸡(狗)中铬含量无显著性差异。     

The Representative Soil Sampling Scheme of England and Wales: a statistical analysis of topsoil nutrient status and pH between 1971 and 2001

The Representative Soil Sampling Scheme of England and Wales has recorded information on the soil of agricultural land in England and Wales since 1969. It is a valuable source of information about the soil in the context of monitoring for sustainable agricultural development. Changes in soil nutrient status and pH were examined over the period 1971–2001. Several methods of statistical analysis were applied to data from the surveys during this period. The main focus here is on the data for 1971, 1981, 1991 and 2001. The results of examining change over time in general show that levels of potassium in the soil have increased, those of magnesium have remained fairly constant, those of phosphorus have declined and pH has changed little. Future sampling needs have been assessed in the context of monitoring, to determine the mean at a given level of confidence and tolerable error and to detect change in the mean over time at these same levels over periods of 5 and 10 years. The results of a non‐hierarchical multivariate classification suggest that England and Wales could be stratified to optimize future sampling and analysis. To monitor soil quality and health more generally than for agriculture, more of the country should be sampled and a wider range of properties recorded.