Relationships between Terrain Features and Forecasting Errors of Surface Wind Speeds in a Mesoscale Numerical Weather Prediction Model

Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.

DEVELOPMENT AND ERROR ANALYSIS OF AN INSPECTING SYSTEM FOR MEASURING THE ROTATIONAL INERTIA OF BULLETS

介绍了一种用于测量弹丸转动惯量的高精度测量仪器，该仪器利用双悬丝扭摆机构、光电计时系统提取摆动周期信息，由MCS-51系列单片机组成的测量系统进行数据处理，并由LED显示器测量结果。文中阐述了仪器的工作原理， 推导了所需的计算公式，分析了产生测量误差的因素，进行了定量精度分析，给出了实验结果与测量精度。

Towards Improving the Quality of Requirement and Testing Process in Agile Software Development:An Empirical Study

Software testing is a critical phase due to misconceptions about ambiguities in the requirements during specification,which affect the testing process.Therefore,it is difficult to identify all faults in software.As requirement changes continuously,it increases the irrelevancy and redundancy during testing.Due to these challenges;fault detection capability decreases and there arises a need to improve the testing process,which is based on changes in requirements specification.In this research,we have developed a model to resolve testing challenges through requirement prioritization and prediction in an agile-based environment.The research objective is to identify the most relevant and meaningful requirements through semantic analysis for correct change analysis.Then compute the similarity of requirements through case-based reasoning,which predicted the requirements for reuse and restricted to error-based requirements.Afterward,the apriori algorithm mapped out requirement frequency to select relevant test cases based on frequently reused or not reused test cases to increase the fault detection rate.Furthermore,the proposed model was evaluated by conducting experiments.The results showed that requirement redundancy and irrelevancy improved due to semantic analysis,which correctly predicted the requirements,increasing the fault detection rate and resulting in high user satisfaction.The predicted requirements are mapped into test cases,increasing the fault detection rate after changes to achieve higher user satisfaction.Therefore,the model improves the redundancy and irrelevancy of requirements by more than 90%compared to other clustering methods and the analytical hierarchical process,achieving an 80%fault detection rate at an earlier stage.Hence,it provides guidelines for practitioners and researchers in the modern era.In the future,we will provide the working prototype of this model for proof of concept.

Convergence analysis for complementary-label learning with kernel ridge regression

Complementary-label learning(CLL)aims at finding a classifier via samples with complementary labels.Such data is considered to contain less information than ordinary-label samples.The transition matrix between the true label and the complementary label,and some loss functions have been developed to handle this problem.In this paper,we show that CLL can be transformed into ordinary classification under some mild conditions,which indicates that the complementary labels can supply enough information in most cases.As an example,an extensive misclassification error analysis was performed for the Kernel Ridge Regression(KRR)method applied to multiple complementary-label learning(MCLL),which demonstrates its superior performance compared to existing approaches.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

Error Analysis of English Pronunciation Acquisition by Chinese Non-English Majors

Chinese non-English majors are a large group of English learners.In the process of English pronunciation acquisition,issues such as incomplete phonological knowledge,transfer of mother tongue,and overgeneralization,lead to confusion of phonemes and stress,misunderstanding of syllable structure,and errors of assimilation,drop,and epenthesis.The accuracy of English pronunciation can only be improved by knowing both English and Chinese phonological systems,strengthening the teaching of English phonological knowledge,and adopting various phonological training activities.

Error Analysis of A New Higher Order Boundary Element Method for A Uniform Flow Passing Cylinders

A higher order boundary element method(HOBEM)is presented for inviscid flow passing cylinders in bounded or unbounded domain.The traditional boundary integral equation is established with respect to the velocity potential and its normal derivative.In present work,a new integral equation is derived for the tangential velocity.The boundary is discretized into higher order elements to ensure the continuity of slope at the element nodes.The velocity potential is also expanded with higher order shape functions,in which the unknown coefficients involve the tangential velocity.The expansion then ensures the continuities of the velocity and the slope of the boundary at element nodes.Through extensive comparison of the results for the analytical solution of cylinders,it is shown that the present HOBEM is much more accurate than the conventional BEM.

A Brief Study of Second Language Learning Strategies From the Perspective of Error Analysis

Language teaching is not a one-way process.It interacts with language learning in an extremely intricate way.To improve language teaching,we need to take the process of language learning into account.This paper tries to explore and understand what strategies the second language learners consciously or subconsciously adopt during their language learning process through the analyses of the linguistic errors they commit,so as to provide some insights into language teaching practice.

An effective method for improving the accuracy of Argo objective analysis

Based on the optimal interpolation objective analysis of the Argo data, improvements are made to the em- pirical formula of a background error covariance matrix widely used in data assimilation and objective anal- ysis systems. Specifically, an estimation of correlation scales that can improve effectively the accuracy of Ar- go objective analysis has been developed. This method can automatically adapt to the gradient change of a variable and is referred to as ＂gradient-dependent correlation scale method＂. Its effect on the Argo objective analysis is verified theoretically with Gaussian pulse and spectrum analysis. The results of one-dimensional simulation experiment show that the gradient-dependent correlation scales can improve the adaptability of the objective analysis system, making it possible for the analysis scheme to fully absorb the shortwave information of observation in areas with larger oceanographic gradients. The new scheme is applied to the Argo data obiective analysis system in the Pacific Ocean. The results are obviously improved.

Analysis on the Reason of Local Heavy Rainstorm Forecast Error in the Subtropical High Control

[Objective] The research aimed to study the reason of local heavy rainstorm forecast error in the subtropical high control. [Method] Started from summarizing the reason of forecast error, by using the conventional ground observation data, the upper air sounding data, T639, T213 and European Center (ECMWF) numerical prediction product data, GFS precipitation forecast product of U.S. National Center for Environmental Prediction, the weather situation, physical quantity field in a heavy rainstorm process which happened in the north of Shaoyang at night on August 5, 2010 were fully analyzed. Based on the numerical analysis forecast product data, the reason of heavy rainstorm forecast error in the subtropical high was comprehensively analyzed by using the comparison and analysis method of forecast and actual situation. [Result] The forecasters didn’t deeply and carefully analyze the weather situation. On the surface, 500 hPa was controlled by the subtropical high, but there was the weak shear line in 700 and 850 hPa. Moreover, they neglected the influences of weak cold air and easterlies wave. The subtropical high quickly weakened, and the system adjustment was too quick. The wind field variations in 850, 700 and 500 hPa which were forecasted by ECMWF had the big error with the actual situation. It was by east about 2 longitudes than the actual situation. In summer forecast, they only considered the intensity and position variations of 500 hPa subtropical high, and neglected the situation variations in the middle, low levels and on the ground. It was the most key element which caused the rainstorm forecast error in the subtropical high. The forecast error of numerical forecast products on the height field situation variation was big. The precipitation forecasts of Japan FSAS, U.S. National Center for Environmental Prediction GFS, T639 and T213 were all small. The humidity field forecast value of T639 was small. In the rainstorm forecast, the local rainstorm forecast index and method weren’t used in the forecast practice. In the precipitation forecast process, they only paid attention to the score prediction of station and didn’t value the non-site prediction. Some important physical quantity factors weren’t carefully studied. [Conclusion] The research provided the reference basis for the forecast and early warning of local heavy rainstorm.

Error Analysis of Adsorption Isotherm Models for Acid Dyes onto Bamboo Derived Activated Carbon

High surface area activated carbons were produced by thermal activation of waste bamboo scaffolding with phosphoric acid.Single component equilibrium dye adsorption was conducted on the carbons produced and compared with a commercially available carbon.Two acid dyes with different molecular sizes,namely Acid Yellow 117(AY117) and Acid Blue 25(AB25),were used to evaluate the adsorption capacity of the produced carbons.It was found that the dye with smaller molecular size,AB 25,was readily adsorbed onto the produced carbon,nearly three times higher than a commercially available carbon,while the larger size dye,AY117,showed little adsorption.The experimental data were analyzed using isotherm equations including Langmuir,Freundlich,Tempkin,Toth,Redlich-Peterson and Sips equations.The equilibrium data were then analyzed using five different non-linear error analysis methods.

ANALYSES OF ERRORS IN MEDIUM-TERM NUMERICAL FORECAST PRODUCTS FOR THE SUBTROPICAL HIGH 1998

By statistic and dynamic analyses, we have come to the following conclusions: (1) The ECMWF medium-term numerical forecast can forecast medium-term activity of subtropical high, and the accuracy rate of forecast cannot have large improvement by translational corrections. (2) The important cause for the ECMWF medium-term numerical forecast to have errors in 1998 is that the astronomical tide is not included in the model. (3) Two indexes are found from which it can be judged that ECMWF medium-term numerical forecast will have errors if the astronomical tide is ignored in the model : ① When the 54.7?line under the moon of the nodical month astronomical singularities coincides with the trough-line of the subtropical jet flow from 50癊 to 150癊 on the 500 hPa level at 2000 L.T. of the same day, and is approximately vertical (α>60? with the isotherm, then the day 0 2 days after the appearance of the nodical month astronomical singularities is defined as the initial day. Then in three successive days after the initial day, ECMWF medium-term numerical forecast of the northern latitude of the 588 line at 120 癊 will have continuous errors as large as two latitudes (7/9). Otherwise, it won’t have continuous errors (13/13). ② Otherwise, if the 54.7 ?line is in the range of a low pressure between two high pressures, then there is a dispersive error on the day of the nodical month astronomical singularities (5/7). There is not any error (6/6) otherwise.

Some of Advances on the Error Analysis in the Frequency Domain for a Digital Simulation Model

This paper surveys a number of recent advances in the error analysis in the frequency domain for a digital simulation model. It is emphasized to discuss the errors in characteristic roots and transfer funcnon of the digital simulation model, the frequency domain errors of the data transfers between thesimulation submodels, and some compensation methods for the errors. Some of the questions to be answered are also presented.

BRIDGE-TOUGHENING ANALYSIS OF THE FIBER REINFORCED COMPOSITE CONTAINING INTERPHASE EFFECT

A detailed fracture mechanics analysis of bridge-toughening in a fiber reinforced composite is presented in this paper. The integral equation governing bridge-toughening as well as crack opening displacement (COD) for the composite with interfacial layer is derived from the Castigliano's theorem and interface shear-lag model. A numerical result of the COD equation is obtained using the iteration solution of the second Fredholm integral equation. In order to investigate the effect of various parameters on the toughening, an approximate analytical solution of the equation is present and its error analysis is performed, which demonstrates the approximate solution to be appropriate. A parametric study of the influence of the crack length, interfacial shear modules, thickness of the interphase, fiber radius, fiber volume fraction and properties of materials on composite toughening is therefore carried out. The results are useful for experimental demonstration and toughening design including the fabrication process of the composite.

Analysis on the Influence of Spring Low Temperature on the Agriculture and the Formation Reason in Liaoning Province in 2010

[Objective] The research aimed to study the influence of spring low temperature on the agriculture and the formation reason in Liaoning Province in 2010. [Method] Based on the synoptics analysis principle, by analyzing the atmospheric circulation situation and satellite cloud map, the influence of spring low temperature on the agriculture and the formation reason of low temperature weather in Liaoning Province during April-May, 2010 were discussed. [Result] The high-altitude situation analysis showed that it was two-trough-two-ridge situation in the high latitude of Eurasia in April, 2010. Ural Mountains high-pressure ridge strengthened to move eastward. Lake Baikal cold air went down toward the southeast along the front of ridge and strengthened into the cold vortex. Liaoning was in the front of cold vortex. Affected by the cold vortex, the temperature in Liaoning area was low. In the first dekad of May, 2010, the activity of cold air was frequent. There were two times cold vortex influence, and the temperature was still low. In the later period of middle dekad of May, the warm ridge entered, and the temperature rose. The high-altitude trough and the low-level jet were the main system and the dynamic condition of precipitation generation respectively. The cold vortex was the main reason of spring continuous low temperature generation, and the secondary reason was the more precipitation. [Conclusion] The research provided the reference basis for the prevention and prediction of spring low temperature in Liaoning Province.

Analysis on Formation Reason of "0902" Blizzard in Northeast China

[Objective]The research aimed to analyze formation reason of ＂ 0902＂ blizzard in northeast China. [Method]By using timely observation data,NCEP reanalysis data and Doppler radar data at Baishan station,blizzard process in southeast part of northeast China during 12-13 February,2009 was analyzed. [Result]Snowfall zone of the blizzard process was wide,snowfall was more,snowfall gradient was big,and snowfall time relatively concentrated. These characteristics reflected that the blizzard process had significant convection characteristics. Baroclinic disturbance at high-altitude straight frontal zone and ground warm frontogenesis caused by eastward movement and northward advancement of North China low vortex at low altitude were the circulation characteristics in the process. Water vapor from the sea went northward as southwest airflow,and strongly converged in blizzard zone,which provided sufficient water vapor condition for the blizzard. Before heavy snowfall occurred,there was accumulation process of heat and energy. Conditional symmetric instability was main unstable mechanism of the blizzard. During heavy snowfall period,ascending branch of secondary vertical circulation at exit zone of high-altitude jet coupled with ascending branch of secondary vertical circulation of warm frontegenesis at low layer,inducing strong development of the vertical motion. Doppler radar intensity echo revealed that it was easy to generate blizzard in the area where echo intensity was consistently above 20 dBz. Strong wind velocity convergence zone at radical velocity field especially adverse wind zone was favorable for the generation of blizzard. [Conclusion]The research could provide reference for blizzard forecast in northeast China.

Error Analysis of Orbit Determination for the Geostationary Satellite with Single Station Antenna Tracking Data

In the study, position and velocity values of a geostationary satellite are found. When performing this, a MATLAB algorithm is used for Runge-Kutta Fehlberg orbit integration method to solve spacecraft’s position and velocity. Integrated method is the solution for the systems which mainly work with a single station. Method provides calculation of azimuth, elevation and range data by using the position simulation results found by RKF. Errors of orbit determination are analysed. Variances of orbit parameters are chosen as the accuracy criteria. Analysis results are the indicator of the method’s

Resolution performance analysis of cumulants-based rank reduction estimator in presence of unexpected modeling errors

Compared to the rank reduction estimator （RARE） based on second-order statistics （called SOS-RARE）, the RARE employing fourth-order cumulants （referred to as FOC-RARE） is capable of dealing with more sources and mitigating the negative influences of the Gaussian colored noise. However, in the presence of unexpected modeling errors, the resolution behavior of the FOC-RARE also deteriorate significantly as SOS-RARE, even for a known array covariance matrix. For this reason, the angle resolution capability of the FOC-RARE was theoretically analyzed. Firstly, the explicit formula for the mathematical expectation of the FOC-RARE spatial spectrum was derived through the second-order perturbation analysis method. Then, with the assumption that the unexpected modeling errors were drawn from complex circular Gaussian distribution, the theoretical formulas for the angle resolution probability of the FOC-RARE were presented. Numerical experiments validate our analytical results and demonstrate that the FOC-RARE has higher robustness to the unexpected modeling en＇ors than that of the SOS-RARE from the resolution point of view.

A Structural Analysis of the Writing Errors Committed by Foundation Students at Arab Open University, Oman

English is considered as Arab students＇ second language which is not used frequently in their daily conversations. Since writing in English is a challenging experience for Omani students, errors in grammar and sentence structures were identified in bridging language courses （foundation level 2） in the field of ESL （English as a Second Language}. Learners＇ errors were considered positively as the best sources to identify students＇ limitations in English writing. The present study investigates the structure errors of Omani students＇ writings in English in foundation level 2 at Arab Open University. The focal aim is to study the errors that Ornani students commit when they are using adjectives ＋ nouns, indefinite articles, and subordinate conjunction ＂because＂. Results show that Omani students committed the following common errors： misplacement of adjectives, omission of the indefinite articles, and wrong structure of the subordinate conjunction （because）. The prime aim of this study is to examine the students＇ aforementioned structural errors which are the result of the interference of their mother-tongue. In order to achieve these aims, students were asked to write two different topics. Finally, this research suggests further recommendations for further studies which might ameliorate students＇ learning by adopting appropriate strategies for teaching.