电脑加油机较大误差来源

电脑加油机越来越受到用户和消费者的欢迎。但也有部分不法分子利用电脑克扣顾客、牟取暴利。依据ＪＪＧ４４３－１９９８燃油加油机计量检定规程，对加油机几种较大误差来源进行分析：１　计量器误差来源 计量器是加油机的心脏，每次检定如发现计量不准，检定员都会微调调量螺杆，来调整加油机的准确度，达到±．３％的允许误差。检定完毕，检定人员应按照规定加印铅封。但部分加油站私自打开铅封或不打开铅封，调换计量器中间的连结块，一台合格计量器使用的是２．０号连接块，有的加油站更换成１．８号或１．５号的连接块，使误差达到２…     

量仪测力仪测量结果的不确定度评定

一、测量过程简述1.测量依据:JJF1134-2005《量仪测力仪检定规程》。2.测量环境条件:温度(10～35)℃,相对湿度不大于80%。3.测量标准:M1级砝码,测量范围1N-15N,其最大允许示值误差为±0.00075N。     

电子秤检定中替代法的使用条件

本文阐述替代法检定大秤量电子衡器的方法，分析误差来源，误差控制范围及替代次数，以解决检定机构标准砝码不足带来的困难。     

对角度仪器示值误差检定的分析研究

角度仪器是工程中常用一种仪器，对其误差大小的把控对相关产品有着极为重要的意义。仪器进行示值误差检定的目的为：一是通过检定找出仪器受检点的误差和仪器的最大误差。二是能分析误差的来源。多面棱体由于结构简单、制造携带方便、精度较高、稳定性较好、易于检定，多年来一直处于角度的实物基准地位。但在精度已无法提升。经论证，两台齿盘差动可以极高精度分别检定角度仪器的整分度、细分度和综合示值误差。     

东北大区平面平晶比对

JJG28—2000《平晶》国家检定规程实施后，东北地区大部分单位未参加规程宣贯会，对规程的理解存在差异，特别是对标准平晶在指定区域内平面度的计算方法存在差异。为了考察东北大区依法设置和授权的计量检定机构平面平晶检定装置的运行情况，保证平面平晶计量的准确可靠，客观、公正、科学地反映目前东北大区依法设置和授权的计量检定机构的平面平晶检定的综合技术水平，规范量值传递过程，保证其量值传递准确一致，东北国家计量测试中心决定进行东北大区内平面平晶比对。     

计量检定中如何处理砝码误差

天平作为常见测量辅助工具的一种,在实验室、工业生产等有关质量测量、计量检定等工作中得到了广泛的应用。借助天平能实现测量结果的直观获取,并为测量精度提供保障。而砝码则是为测量提供准确性保障的重要工具之一,有利于天平检定实效的提升,因此需以天平砝码为对象,定期开展检定工作。文章以天平砝码检定误差类型为切入点,对砝码计量检定误差原因进行了分析,并在此基础上提出了合理有效的应对策略,以期提高测量精确度。     

万工显示值误差检定方法误差分析

万工显示值误差检定方法误差分析桂林市计量测试研究所林伟光万工显是一种多用途的光学机械式两坐标测量仪器，它构造较复杂，影响示值误差的因素也较多。万工显检定方法的误差主要因素有：温度、标尺精度以及对线与读数精度等，其误差分析如下：ｌ、温度误差δＬ当仪器标...     

浅谈出租车计价器使用误差的检定

浅谈出租车计价器使用误差的检定雷衍夫按照ＪＪＧ５１７——８８（出租汽车计价器检定规程》要求，对出租汽车计价器的检定分别为本机误差、使用误差和等侯时间误差的检定．本机误差、等候时间误差的检定华须在计价器安装在车辆上以前进行．当计价器安装到车辆上以后只进...     

光栅式表类量具检定仪的研制

光栅式表类量具检定仪的研制张洪连，刘彦明一、光栅式表类量具检定仪的误差要求为了改变目前沿用的机械式表类量具检定仪检定误差大、工作效率低的现状，我们研制了光栅式表类量具检定仪。为使光栅式表类量具检定仪能同时满足百分表、千分表的检定要求，根据ＪＪＧ３４５...     

万能显微镜示值误差的检定

万能显微镜示值误差检定的特点是利用标准刻线尺进行比较检定。其检定方法和误差分析如下：     

研发投入与我国高新技术产品出口关系的实证分析

基于协整理论和误差修正模型,对R&D投入与我国高新技术产品出口的长期与短期关系做了相关性分析。分析结果表明了R&D投入能对我国高新技术产品出口起促进和推动作用。政府应当推动建立有利于创新的制度环境和激励机制,鼓励企业开展技术创新并提供优惠政策,支持和培育企业出口具有自主知识产权和自主品牌的商品,提高出口商品附加值,同时采取切实有效的措施,努力创建技术蓝领大军。     

Competing Environmental Labels

We study markets in which consumers prefer green products but cannot determine the environmental quality of any given firm's product on their own. A nongovernmental organization (NGO) can establish a voluntary standard and label products that comply with it. Alternatively, industry can create its own standard and label. We compare the stringency of these two types of labels, and study their strategic interaction when they coexist. We find that even with error‐free labels, environmental benefits may be smaller with two labels than with the NGO label alone, and we characterize when label competition is more likely to be environmentally beneficial.     

Tests of the money-output relation using disaggregated data

Either anticipated or unanticipated money affects output in fourteen of twenty U.S. manufacturing industries. In most of these instances, however, Akaike's final prediction error criterion indicates that money enters an industry's output equation with lags of three months or less. For just two industries, tobacco manufacturing and textile mill products, are there clear indications that money is not neutral at extended lags. Each of these industries is concentrated in one or two states suggesting that monetary policy may affect output through a regional credit channel.     

Finite sample properties of maximum likelihood estimator in spatial models

We investigate the finite sample properties of the maximum likelihood estimator for the spatial autoregressive model. A stochastic expansion of the score function is used to develop the second-order bias and mean squared error of the maximum likelihood estimator. We show that the results can be expressed in terms of the expectations of cross products of quadratic forms, or ratios of quadratic forms in a normal vector which can be evaluated using the top order invariant polynomial. Our numerical calculations demonstrate that the second-order behaviors of the maximum likelihood estimator depend on the degree of sparseness of the weights matrix.     

发动机凸轮升程误差曲线符合“最小条件”的评定准则

无论以何种方法和何种方式所获得的升级误差曲线，均含有位置误差引起的升程误。这项误差，属系统误差，必须从检测结果予以剔除，才能真实反映凸轮的形状误差。凸轮升程误差符合最小条件的评定准则，正是为剔除置误差引起的升程误差而提出的。     

数控机床空间几何误差识别与检测

分析了国内外误差参数识别的方法,详细介绍了四线法识别和检测数控机床空间几何误差的过程和步骤,通过分析四线法的识别机床误差的工程,进一步识别数控机床空间几何误差的各项误差元素。为后续机床误差补偿提供理论依据。     

Regression analysis on serial dilution data from virus validation robustness studies

To ensure the safety of plasma-derived medicinal products, the Dutch Blood Supply Foundation (Sanquin) performs virus validation experiments. Data from these experiments are based on serial dilution assays. Regression analysis on assay data faces several problems: only a small number of data points are available, data contain censoring and are subject to sampling error. Furthermore, the process variability inherent to the experiments is not evident. In this paper we address these problems by introducing a regression model for serial dilution data and by analyzing how validation experiments and simulation techniques can help elucidate various sources of variability the experiments are subject to. These are then incorporated into the regression model.     

Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana

The major challenge in managing blood products lies in the uncertainty of blood demand and supply, with a trade-off between shortage and wastage, especially in most developing countries. Thus, reliable demand predictions can be imperative in planning voluntary blood donation campaigns and improving blood availability within Ghana hospitals. However, most historical datasets on blood demand in Ghana are predominantly contaminated with missing values and outliers due to improper database management systems. Consequently, time-series prediction can be challenging since data cleaning can affect models’ predictive power. Also, machine learning (ML) models’ predictive power for backcasting past years’ lost data is understudied compared to their forecasting abilities. This study thus aims to compare K-Nearest Neighbour regression (KNN), Generalised Regression Neural Network (GRNN), Neural Network Auto-regressive (NNAR), Multi-Layer Perceptron (MLP), Extreme Learning Machine (ELM) and Long Short-Term Memory (LSTM) models via a rolling-origin strategy, for forecasting and backcasting a blood demand data with missing values and outliers from a government hospital in Ghana. KNN performed well in forecasting blood demand (12.55% error); whereas, ELM achieved the highest backcasting power (19.36% error). Future studies can also employ ML algorithms as a good alternative for backcasting past values of time-series data that are time-reversible.     

煤炭化验误差及处理分析

基于本人多年从事煤炭化验的工作经验,通过对煤炭化验误差的来源分析,从更新检测设备、采样制样及化验过程中的误差处理三方面来探讨如何降低与减少煤炭化验的误差。     

Evaluating estimation methods for ordinal data in structural equation modeling

This study examined the performance of two alternative estimation approaches in structural equation modeling for ordinal data under different levels of model misspecification, score skewness, sample size, and model size. Both approaches involve analyzing a polychoric correlation matrix as well as adjusting standard error estimates and model chi-squared, but one estimates model parameters with maximum likelihood and the other with robust weighted least-squared. Relative bias in parameter estimates and standard error estimates, Type I error rate, and empirical power of the model test, where appropriate, were evaluated through Monte Carlo simulations. These alternative approaches generally provided unbiased parameter estimates when the model was correctly specified. They also provided unbiased standard error estimates and adequate Type I error control in general unless sample size was small and the measured variables were moderately skewed. Differences between the methods in convergence problems and the evaluation criteria, especially under small sample and skewed variable conditions, were discussed.