基于动态冲击试验的通勤类飞机座椅符合性验证技术

国产某型民用通勤类飞机为了取得欧洲航空安全局(EASA)型号合格证,机上座椅需进行设计更改并补充进行应急着陆情况下的动态要求符合性验证.通过对适航条款及相应标准的解读,研究了基于动态试验的航空座椅动态要求适航验证技术,其主要包括座椅动态性能基本要求、试验构型及工况筛选、试验规划、合格判据和试验结果分析等内容.结果表明,该型机旅客座椅满足适航规章对座椅的动态性能要求.该项旅客座椅动态性能试验的成功为型号取得EASA型号合格证奠定了良好的基础,该型飞机也即将成为第一个取得欧洲型号合格证的国产飞机.     

Panel LM unit root tests with level and trend shifts

This paper considers a Lagrange multiplier (LM) based panel unit root test that allows for heterogeneous structural breaks in both the intercepts and slopes of a series. We note that many popular time series variables are likely to exhibit changing means and/or trends over time. Given that the usual tests will depend on the nuisance parameters indicating the locations of the trend breaks, we adopt a transformation procedure that makes our new panel unit root tests invariant to the nuisance parameters. To illustrate the importance of the power gain provided by our test, we examine the convergence hypothesis using relative ratios of per capita health care expenditures in 20 OECD countries. Our results provide evidence that the convergence hypothesis is supported.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

基于效应的随机灰规划模型和应用

为了解决同时含有随机因素和灰色因素的不确定规划问题,通过结合区间灰数所属区间两个端点的随机性,给出随机区间灰数和随机区间灰函数的定义,提出了随机灰规划模型。通过综合效应函数理论用随机变量期望值和方差综合量化表示灰数所属区间的两个端点值。应用该理论对综合量化后的两个端点值继续进行综合量化,从而将随机灰规划转化为确定型规划问题。应用遗传算法进行求解。通过综合效应函数的理念,综合随机变量的期望和方差,同时综合区间灰数的区间因素,将随机灰规划数学模型转化为确定型规划模型即基于效应的随机灰规划模型。通过选取不同的综合效应函数,得到了关于不同决策意识下的随机灰规划的最优解。这个方法可为决策者进行不确定决策提供参考。     

Beyond Single-Factor Affine Term Structure Models

This article proposes a new approach to testing for the hypothesisof a single priced risk factor driving the term structure ofinterest rates. The method does not rely on any parametric specificationof the state variable dynamics or the market price of risk.It simply exploits the constraint imposed by the no-arbitragecondition on instantaneous expected bond returns. In order toachieve our goal, we develop a Kolmogorov-Smirnov test and applyit to data on Treasury bills and bonds for both the United Statesand Spain. We find that the single risk factor hypothesis cannotbe rejected for either dataset.     

The Importance of Professional Training for Test Writers

The importance of language testing is noticed by more and more people.But the quality of testing,or say,the level of test writers,has been ignored for a long time.This article intends to talk about the importance of professional training for test writ- ers,in order to arouse people＇s attention to the quality of test designers.     

标准化在油藏监测工作中的作用

以油藏监测工作中的油藏压力监测为例，介绍了标准化工作在压力资料录取及解释分析中的作用。并用实例说明了标准化作业在油田开发方案的制定及油藏压力监测中的应用。     

Predicting the geo-temporal variations of crime and disorder

Traditional police boundaries—precincts, patrol districts, etc.—often fail to reflect the true distribution of criminal activity and thus do little to assist in the optimal allocation of police resources. This paper introduces methods for crime incident forecasting by focusing upon geographical areas of concern that transcend traditional policing boundaries. The computerised procedure utilises a geographical crime incidence-scanning algorithm to identify clusters with relatively high levels of crime (hot spots). These clusters provide sufficient data for training artificial neural networks (ANNs) capable of modelling trends within them. The approach to ANN specification and estimation is enhanced by application of a novel and noteworthy approach, the Gamma test (GT).     

A comparison of several approximations to the power function of the likelihood ratio test in covariance structure analysis*

In this paper we compare alternative asymptotic approximations to the power of the likelihood ratio test used in covariance structure analysis for testing the fit of a model. Alternative expressions for the noncentrality parameter (ncp) lead to different approximations to the power function. It appears that for alternative covariance matrices close to the null hypothesis, the alternative ncp's lead to similar values, while for alternative covariance matrices far from H_o the different expressions for the ncp can conflict substantively. Monte Carlo evidence shows that the ncp proposed in Satorra and Saris (1985) gives the most accurate power approximations.